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CODEOWNERS

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+#ECCN:Open Source

CODE_OF_CONDUCT.md

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+# Salesforce Open Source Community Code of Conduct
+
+## About the Code of Conduct
+
+Equality is a core value at Salesforce. We believe a diverse and inclusive
+community fosters innovation and creativity, and are committed to building a
+culture where everyone feels included.
+
+Salesforce open-source projects are committed to providing a friendly, safe, and
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+The goal of this code of conduct is to specify a baseline standard of behavior so
+that people with different social values and communication styles can work
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+It also establishes a mechanism for reporting issues and resolving conflicts.
+
+All questions and reports of abusive, harassing, or otherwise unacceptable behavior
+in a Salesforce open-source project may be reported by contacting the Salesforce
+Open Source Conduct Committee at [email protected].
+
+## Our Pledge
+
+In the interest of fostering an open and welcoming environment, we as
+contributors and maintainers pledge to making participation in our project and
+our community a harassment-free experience for everyone, regardless of gender 
+identity and expression, sexual orientation, disability, physical appearance, 
+body size, ethnicity, nationality, race, age, religion, level of experience, education, 
+socioeconomic status, or other similar personal characteristics.
+
+## Our Standards
+
+Examples of behavior that contributes to creating a positive environment
+include:
+
+* Using welcoming and inclusive language
+* Being respectful of differing viewpoints and experiences
+* Gracefully accepting constructive criticism
+* Focusing on what is best for the community
+* Showing empathy toward other community members
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+Examples of unacceptable behavior by participants include:
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+* The use of sexualized language or imagery and unwelcome sexual attention or
+advances
+* Personal attacks, insulting/derogatory comments, or trolling
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+* Other conduct which could reasonably be considered inappropriate in a
+professional setting
+* Advocating for or encouraging any of the above behaviors
+
+## Our Responsibilities
+
+Project maintainers are responsible for clarifying the standards of acceptable
+behavior and are expected to take appropriate and fair corrective action in
+response to any instances of unacceptable behavior.
+
+Project maintainers have the right and responsibility to remove, edit, or
+reject comments, commits, code, wiki edits, issues, and other contributions
+that are not aligned with this Code of Conduct, or to ban temporarily or
+permanently any contributor for other behaviors that they deem inappropriate,
+threatening, offensive, or harmful.
+
+## Scope
+
+This Code of Conduct applies both within project spaces and in public spaces
+when an individual is representing the project or its community. Examples of
+representing a project or community include using an official project email
+address, posting via an official social media account, or acting as an appointed
+representative at an online or offline event. Representation of a project may be
+further defined and clarified by project maintainers.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported by contacting the Salesforce Open Source Conduct Committee 
+at [email protected]. All complaints will be reviewed and investigated 
+and will result in a response that is deemed necessary and appropriate to the 
+circumstances. The committee is obligated to maintain confidentiality with 
+regard to the reporter of an incident. Further details of specific enforcement 
+policies may be posted separately.
+
+Project maintainers who do not follow or enforce the Code of Conduct in good
+faith may face temporary or permanent repercussions as determined by other
+members of the project's leadership and the Salesforce Open Source Conduct 
+Committee.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][contributor-covenant-home],
+version 1.4, available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html. 
+It includes adaptions and additions from [Go Community Code of Conduct][golang-coc], 
+[CNCF Code of Conduct][cncf-coc], and [Microsoft Open Source Code of Conduct][microsoft-coc].
+
+This Code of Conduct is licensed under the [Creative Commons Attribution 3.0 License][cc-by-3-us].
+
+[contributor-covenant-home]: https://www.contributor-covenant.org (https://www.contributor-covenant.org/)
+[golang-coc]: https://golang.org/conduct
+[cncf-coc]: https://github.com/cncf/foundation/blob/master/code-of-conduct.md
+[microsoft-coc]: https://opensource.microsoft.com/codeofconduct/
+[cc-by-3-us]: https://creativecommons.org/licenses/by/3.0/us/

Dataset_Stats.csv

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+Category,Data_name,Index,Year,License,Train,Validation,Test,Total
+Natural Language Understanding,ATIS,1,Speed and NLP 1990,"GNU General Public License, version 2",4478,500,893,5871
+Natural Language Understanding,ATIS-NER,2,Speed and NLP 1990,"GNU General Public License, version 2",4478,500,893,5871
+Natural Language Understanding,BANKING77,3,ACL 2020 NLP4ConvAI,CC BY 4.0,8622,1540,3080,13242
+Natural Language Understanding,BANKING77-OOS,4,ACL 2020 NLP4ConvAI,CC BY 4.0,5905,1506,2000,9411
+Natural Language Understanding,CLINC-Single-Domain-OOS-banking,5,EMNLP 2020,CC BY 3.0,500,500,500,1500
+Natural Language Understanding,CLINC-Single-Domain-OOS-credit_cards,6,EMNLP 2021,CC BY 3.0,500,500,500,1500
+Natural Language Understanding,CLINC150,7,EMNLP 2019,CC BY 3.0,15000,3000,4500,22500
+Natural Language Understanding,DSTC8-SGD,8,ACL 2020,CC BY-SA 4.0,1402,0,481,1883
+Natural Language Understanding,HWU64,9,IWSDS 2019,CC BY 4.0,8954,1076,1076,11106
+Natural Language Understanding,MIT-Movie,10,ICASSP 2013,BSD license,17590,0,4395,21985
+Natural Language Understanding,MIT-Restaurant,11,ICASSP 2014,BSD license,7660,0,1521,9181
+Natural Language Understanding,RESTAURANTS8K,12,ACL 2020,CC BY 4.0,4613,0,2379,6992
+Natural Language Understanding,SNIPS,13,ArXiv 2018,Apache License 2.0,13084,700,700,14484
+Natural Language Understanding,SNIPS-NER,14,ArXiv 2018,Apache License 2.0,13084,700,700,14484
+Natural Language Understanding,TOP,15,EMNLP 2018,CC-BY-SA,31279,0,9042,40321
+Natural Language Understanding,TOP-NER,16,EMNLP 2018,CC-BY-SA,31279,0,9042,40321
+Task Oriented Dialogue,ABCD,17,NAACL 2021,MIT License,8034,1004,1004,10042
+Task Oriented Dialogue,AirDialogue,18,EMNLP 2018,Apache License Version 2.0,321459,40363,0,361822
+Task Oriented Dialogue,BiTOD,19,NeurIPS 2021 Workshop,Apache License 2.0,2952,295,442,3689
+Task Oriented Dialogue,CaSiNo,20,NAACL 2021,CC BY 4.0,900,30,100,1030
+Task Oriented Dialogue,CraigslistBargains,21,EMNLP 2018,MIT License,4000,570,803,5373
+Task Oriented Dialogue,Disambiguation,22,NAACL 2022,MiT License,8433,999,1000,10432
+Task Oriented Dialogue,DSTC2-Clean,23,ACL 2018,"GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007",1612,506,1117,3235
+Task Oriented Dialogue,FRAMES,24,SIGDIAL 2017,"GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007",1329,0,40,1369
+Task Oriented Dialogue,GECOR,25,EMNLP 2019,CC BY 4.0,676,0,0,676
+Task Oriented Dialogue,HDSA-Dialog,26,ACL 2019,MIT License,8438,1000,1000,10438
+Task Oriented Dialogue,KETOD,27,NAACL 2022,MiT License,4247,545,532,5324
+Task Oriented Dialogue,KVRET,28,SIGDIAL 2017,No License,2425,302,304,3031
+Task Oriented Dialogue,MetaLWOZ,29,Sigdial 2019,MICROSOFT RESEARCH LICENSE TERMS,37884,0,2319,40203
+Task Oriented Dialogue,MS-DC,30,Arxiv 2018,MICROSOFT RESEARCH LICENSE TERMS,10000,0,0,10000
+Task Oriented Dialogue,MuDoCo,31,LREC 2020,Attribution-NonCommercial 4.0 International,6058,691,749,7498
+Task Oriented Dialogue,MulDoGO,32,EMNLP 2019,Community Data License Agreement – Permissive – Version 1.0,59939,1150,2319,63408
+Task Oriented Dialogue,MultiWOZ_2.1,33,LREC 2020,MiT License,8434,999,1000,10433
+Task Oriented Dialogue,MULTIWOZ2_2,34,ACL NLP4CONV AI,Mit License,8437,1000,1000,10437
+Task Oriented Dialogue,SGD,35,AAAI 2020,CC BY-SA 4.0,16142,2482,4201,22825
+Task Oriented Dialogue,SimJointGEN,36,NAACL 2020,No license,100000,10000,10000,120000
+Task Oriented Dialogue,SimJointMovie,37,NAACL 2018,No license,384,120,264,768
+Task Oriented Dialogue,SimJointRestaurant,38,NAACL 2019,No license,1116,349,775,2240
+Task Oriented Dialogue,STAR,39,CL 2020,MIT License,6652,0,0,6652
+Task Oriented Dialogue,Taskmaster1,40,EMNLP 2019,Attribution 4.0 International (CC BY 4.0),6170,769,769,7708
+Task Oriented Dialogue,Taskmaster2,41,Github 2020,Creative Commons Attribution 4.0 License (CC BY 4.0),17304,0,0,17304
+Task Oriented Dialogue,Taskmaster3,42,Github 2020,Creative Commons Attribution 4.0 License (CC BY 4.0),22724,17019,17903,57646
+Task Oriented Dialogue,WOZ2_0,43,ACL 2017,Apache License 2.0,600,200,400,1200
+Dialogue Summarization,AMI,44,ICASSP 2005,Creative Commons Attribution 4.0 International Licence (CC BY 4.0),117054,0,0,117054
+Dialogue Summarization,CRD3,45,ACL2021,CC BY-SA 4.0,108,16,16,140
+Dialogue Summarization,DialogSum,46,ACL 2020,CC BY-SA 4.0,12460,500,500,13460
+Dialogue Summarization,ECTSum,47,Findings of ACL21,MIT License,1681,249,495,2425
+Dialogue Summarization,ICSI,48,EMNLP 2022,No License,110254,0,0,110254
+Dialogue Summarization,MediaSum,49,ICASSP 2005, CC BY 4.0,443596,10000,10000,463596
+Dialogue Summarization,QMSum,50,NAACL 2021,No license,162,35,35,232
+Dialogue Summarization,SAMSum,51,NAACL 2021,non-commercial licence: CC BY-NC-ND 4.0,14732,818,819,16369
+Dialogue Summarization,TweetSumm,52,EMNLP19,Creative Commons Zero v1.0 Universal,879,110,110,1099
+Dialogue Summarization,ConvoSumm,53,ACL 2022,No License,821,200,1000,2021
+Dialogue Summarization,SummScreen_ForeverDreaming,54,ACL 2022,No License,3673,338,337,4348
+Dialogue Summarization,SummScreen_TVMegaSite,55,COLING20,Creative Commons Legal CodeCC0 1.0 Universal,18915,1795,1793,22503
+Conversational Recommendation,Redial,56,EMNLP 2021,"Apache License 2.0,",10006,0,1342,11348
+Conversational Recommendation,INSPIRED,57,EMNLP 2020,No License,800,100,100,1000
+Conversational Recommendation,DuRecDial-2.0,58,ACL 2019,CC-BY-NC-4.0,5678,811,1752,8241
+Conversational Recommendation,OpenDialKG,59,NeurIPS 2018,CC BY 4.0,12302,0,0,12302
+Conversational Recommendation,SalesBot,60,ACL 2022,No License,10277,0,0,10277
+Open Domain Dialogue,AntiScam,61,AAAI 2020,MiT License,220,0,0,220
+Open Domain Dialogue,chitchat-dataset,62,ICAART 2020,MiT License,4018,0,0,4018
+Open Domain Dialogue,ConvAI2,63,DSTC 2019,Apache 2.0,2423,0,0,2423
+Open Domain Dialogue,Empathetic,64,ACL 2019,cc-by-nc-4.0,17802,2761,2541,23104
+Open Domain Dialogue,HH-RLHF,65,Arxiv 2022,MiT License,160800,0,8552,169352
+Open Domain Dialogue,PLACES3.5,66,EACL 2023,CC BY-NC 4.0,5591,0,0,5591
+Open Domain Dialogue,Prosocial,67,EMNLP 2022,MiT License,42304,7132,8701,58137
+Open Domain Dialogue,SODA,68,Arxiv 2023,Mit License,1191582,146346,148968,1486896
+Knowledge Grounded Dialogue,CompWebQ,69,NAACL 2018,"GNU General Public License, version 2",27639,703,2816,31158
+Knowledge Grounded Dialogue,CoQA,70,TACL 2019,MiT License,7199,500,0,7699
+Knowledge Grounded Dialogue,CoSQL,71,EMNLP 2019,CC BY-SA 4.0,4318,586,0,4904
+Knowledge Grounded Dialogue,DART,72,NAACL 2021,MIT License,62659,2768,5097,70524
+Knowledge Grounded Dialogue,FeTaQA,73,TACL 2022,CC BY-SA 4.0,7326,1001,2003,10330
+Knowledge Grounded Dialogue,GrailQA,74,WWW 2021,Apache License 2.0,44337,300,6463,51100
+Knowledge Grounded Dialogue,HybridQA,75,EMNLP 2020,MIT License,62682,3466,0,66148
+Knowledge Grounded Dialogue,MTOP,76,EACL 2021,CC BY-SA 4.0,15667,2235,4386,22288
+Knowledge Grounded Dialogue,MultiModalQA,77,ICLR 2021,No License,15688,1501,0,17189
+Knowledge Grounded Dialogue,SParC,78,ACL 2019,CC BY-SA 4.0,6064,844,0,6908
+Knowledge Grounded Dialogue,Spider,79,EMNLP 2018,CC BY-SA 4.0,7000,1034,0,8034
+Knowledge Grounded Dialogue,SQA,80,ACL 2017,CC BY-SA 4.0,4257,784,1025,6066
+Knowledge Grounded Dialogue,ToTTo,81,EMNLP 2020,CC BY-SA 3.0,120761,7700,0,128461
+Knowledge Grounded Dialogue,WebQSP,82,ACL 2016,No License,2673,309,1639,4621
+Knowledge Grounded Dialogue,WikiSQL,83,ArXiv 2017,BSD 3-Clause License,56355,8421,15878,80654
+Knowledge Grounded Dialogue,WikiTQ,84,ACL 2015,CC BY-SA 4.0,11321,2831,4344,18496
+Knowledge Grounded Dialogue,wizard_of_internet,85,ACL 2022,CC BY 4.0,8614,0,503,9117
+Knowledge Grounded Dialogue,wizard_of_wikipedia,86,ICLR 2019,CC BY 4.0,18430,967,968,20365

LICENSE.txt

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README.md

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+<p align="center">
+    <br>
+    <img src="figures/logo.png" width="510"/>
+    <br>
+<!-- <p>
+<div align="center"> -->
+<a href="https://arxiv.org/abs/2307.10172" style="font-size:20px;">Paper</a>,
+<a href="https://huggingface.co/datasets/Salesforce/dialogstudio" style="font-size:20px;">Huggingface</a>,
+<a href="#model" style="font-size:20px;">Model</a>,
+<a href="https://twitter.com/JianguoZhang3" style="font-size:20px">Twitter</a> 
+<!-- </div> -->
+<p>
+
+# DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection and Instruction-Aware Models for Conversational AI
+
+## News!
+
+* [Initial Release] July 2023, we're thrilled to the initial release of the largest unified Dialog dataset collection. The full list of all available datasets is [here](./Dataset_Stats.csv).  
+
+
+## Contents
+
+- [Introduction](#introduction)
+- [Loading Data](#loading-data)
+- [Datasets](#datasets)
+- [Model](#model)
+- [License](#license)
+- [Citation](#citation)
+
+## Introduction
+
+<!-- Check [DialogStudio_datasets.csv](https://docs.google.com/spreadsheets/d/10U9I4GoHFTYxl3OlzbbV0gmXerMT9Itn2MZs8t6AIK0/edit#gid=461625820) for all supported datasets. -->
+DialogStudio is a large collection and unified dialog datasets. 
+The figure below provides a summary of the general statistics associated with DialogStudio. DialogStudio unified each dataset while preserving its original information, and this aids in supporting research on both individual datasets and Large Language Model (LLM) training. The full list of all available datasets is [here](./Dataset_Stats.csv).
+
+The data are downloadable through Huggingface as introduced in [Loading Data](#loading-data). We also provide examples for each dataset in this repo. For more granular and category-specific details, please refer to the individual folders corresponding to each category within the DialogStudio collection, e.g. [MULTIWOZ2_2](./task-oriented-dialogues/MULTIWOZ2_2/) dataset under the [task-oriented-dialogues](./task-oriented-dialogues/) category. 
+<p align="center">
+    <br>
+    <img src="figures/DialogStudio_Stats.png" width="730"/>
+    <br>
+<p>
+
+DialogStudio evaluates dialogue quality based on six critical criteria, namely Understanding, Relevance, Correctness, Coherence, Completeness, and Overall Quality. Each criterion is scored on a scale of 1 to 5, with the highest scores reserved for exceptional dialogues.
+
+Given the vast number of datasets incorporated into DialogStudio, we utilized 'gpt-3.5-turbo' to assess 33 distinct datasets. The corresponding script used for this evaluation can be accessed through the [link](https://github.com/salesforce/DialogStudio/blob/main/code/openai_dialog_quality_evaluation.py). 
+
+The results of our dialogue quality assessment are presented below. We intend to release evaluation scores for individually selected dialogues in the upcoming period.
+<p align="center">
+    <br>
+    <img src="figures/DialogStudio_Quality_Scores.png" width="700"/>
+    <br>
+<p>
+
+
+## Loading Data
+
+You can load any dataset in the DialogStudio from the [HuggingFace hub](https://huggingface.co/datasets/Salesforce/dialogstudio) by claiming the `{dataset_name}`, which is exactly the dataset folder name. All available datasets are described in [dataset content](./Dataset_Stats.csv).
+
+Below is one example to load the [MULTIWOZ2_2](./task-oriented-dialogues/MULTIWOZ2_2/) dataset under the [task-oriented-dialogues](./task-oriented-dialogues/) category:
+
+<!-- Agree Licenses on the [HuggingFace hub](https://huggingface.co/datasets/Salesforce/dialogstudio). Ensure you're also logged into your HuggingFace account on local. If you haven't logged in yet, you can do so by running the following command in your terminal:
+```python
+huggingface-cli login
+``` -->
+
+Load the dataset
+```python
+from datasets import load_dataset
+
+dataset = load_dataset('Salesforce/dialogstudio', 'MULTIWOZ2_2')
+```
+Here is the output structure of MultiWOZ 2.2
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['original dialog id', 'new dialog id', 'dialog index', 'original dialog info', 'log', 'prompt', 'external knowledge non-flat', 'external knowledge', 'dst knowledge', 'intent knowledge'],
+        num_rows: 8437
+    })
+    validation: Dataset({
+        features: ['original dialog id', 'new dialog id', 'dialog index', 'original dialog info', 'log', 'prompt', 'external knowledge non-flat', 'external knowledge', 'dst knowledge', 'intent knowledge'],
+        num_rows: 1000
+    })
+    test: Dataset({
+        features: ['original dialog id', 'new dialog id', 'dialog index', 'original dialog info', 'log', 'prompt', 'external knowledge non-flat', 'external knowledge', 'dst knowledge', 'intent knowledge'],
+        num_rows: 1000
+    })
+})
+```
+ 
+
+## Datasets
+
+The datasets are split into several categories in this GitHub repository and [HuggingFace hub](https://huggingface.co/datasets/Salesforce/dialogstudio). You can check the [table of dataset](./Dataset_Stats.csv) for more information. And you can click into each folder to check a few examples:
+
+- [Knowledge-Grounded-Dialogues](./knowledge-grounded-dialogues/)
+- [Natural-Language-Understanding](./natural-language-understanding/)
+- [Open-Domain-Dialogues](./open-domain-dialogues/)
+- [Task-Oriented-Dialogues](./task-oriented-dialogues/)
+- [Dialogue-Summarization](./dialogue-summarization/)
+- [Conversational-Recommendation-Dialogs](./conversational-recommendation-dialogues/)
+
+<!-- ```
+Datasets/
+├── Knowledge-Grounded-Dialogues
+├── Natural-Language-Understanding
+├── Open-Domain-Dialogues
+├── Task-Oriented-Dialogues
+├── Dialogue-Summarization
+├── Conversational-Recommendation-Dialogs
+``` -->
+
+
+## Model
+(Will update soon)
+
+We've rolled out version 1.0 of models trained on a few selected DialogStudio datasets. Built on small-scale pre-trained models, this version does not incorporate datasets utilized for training large-scale models (>=7B) like Alpaca, ShareGPT, GPT4ALL, UltraChat from OpenAI's 'GPT-3.5/4', or other datasets such as OASST1 and WizardCoder (Note that DialogStudio has unified such datasets).  As a result, it has certain limitations in terms of writing and creative capabilities. Our initial focus is to update the model versions to enhance existing abilities. Further improvements, including expansion of other capabilities, are part of our roadmap and will be responsive to community requests.
+
+
+## License
+
+Our project follows the following structure with respect to licensing:
+
+1. For all the modified datasets in DialogStudio: 
+   - A portion of these datasets is under the [Apache License 2.0](LICENSE.txt).
+   - Some retain their original licenses even after modification.
+   - For a few datasets that lacked a license, we have cited the relevant papers.
+2. Original dataset licenses: For reference, we also put the originally available licenses for each dataset into their respective dataset folders.
+3. Code: Our codebase is under the [Apache License 2.0](LICENSE.txt).
+
+For detailed licensing information, please refer to the specific licenses accompanying the datasets. It is important to familiarize yourself with these terms as we do not assume responsibility for licensing issues.
+
+## Acknowledgement
+We sincerely thank all dataset authors who have contributed to the Conversational AI field. Despite careful efforts, inaccuracies in our citations or references may occur. If you spot any errors or omissions, please raise an issue or submit a pull request to help us improve. Thank you!
+
+## Citation
+
+The data and code in this repository is mostly developed for or derived from the paper below. If you utilize datasets from DialogStudio, we kindly request you cite both the original work and our own.
+
+```
+@misc{zhang2023dialogstudio,
+      title={DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI}, 
+      author={Jianguo Zhang and Kun Qian and Zhiwei Liu and Shelby Heinecke and Rui Meng and Ye Liu and Zhou Yu and and Huan Wang and Silvio Savarese and Caiming Xiong},
+      year={2023},
+      eprint={2307.10172},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+
+## Contribution
+
+We enthusiastically invite contributions from the community! Join us in our shared mission to propel the field of conversational AI forward!

SECURITY.md

@@ -0,0 +1,7 @@
+## Security
+
+Please report any security issue to [[email protected]](mailto:[email protected])
+as soon as it is discovered. This library limits its runtime dependencies in
+order to reduce the total cost of ownership as much as can be, but all consumers
+should remain vigilant and have their security stakeholders review all third-party
+products (3PP) like this one and their dependencies.

code/openai_dialog_quality_evaluation.py

@@ -0,0 +1,101 @@
+"""
+ Copyright (c) 2023, salesforce.com, inc.
+ All rights reserved.
+ SPDX-License-Identifier: Apache License 2.0
+ For full license text, see the LICENSE file in the repo root or https://www.apache.org/licenses/LICENSE-2.0
+"""
+
+
+import os
+os.environ["OPENAI_API_KEY"] = ""
+
+
+from langchain.chains.llm import LLMChain
+from langchain.prompts import PromptTemplate
+from langchain.chat_models import ChatOpenAI
+import json
+from utils import open_json, save_json, open_jsonl
+from collections import defaultdict
+
+class EvaluateDialogs(object):
+    """ Evaluate Dialogs based on OpenAI. To run this:
+        pip install openai
+        pip install langchain
+    """
+    def __init__(self):
+        self.data_dir = "/Users/jianguozhang/TOD-Family/TOD-Studio/open-source/"
+        self.excluded_datasets = ['MetaLWOZ', "MuDoCo", "SalesBot", "HDSA-Dialog", "MULTIWOZ2_2"]  # "SGD"
+
+        self.quality_agent_prompt = PromptTemplate(
+            input_variables=["dialog"],
+            template="""
+            Hi AI, I plan to train a language model for response generation. Please analyze the following dialogue and evaluate it based on the criteria provided. Assign a score from 1 (poor) to 5 (excellent) for each category. We're looking for a critical assessment, and higher scores should only be given to truly exceptional examples. The criteria for evaluation are: Understanding, Relevance, Completeness, Correctness, and Coherence.
+        
+            After your assessment, provide an overall score for the dialogue along with a concise summary  of your evaluation. The overall score should also be on a scale of 1 (poor) to 5 (excellent) and should represent a holistic assessment of the dialogue.
+            
+            Please present your evaluation and comment into the following format:
+            
+            {{
+              "Understanding": _,
+              "Relevance": _,
+              "Completeness": _,
+              "Correctness": _,
+              "Coherence": _,
+              "Overall": {{"score": _, "comment": _}}
+            }}
+            
+            Please replace each underscore (_) with the appropriate score. For the 'Overall' field, provide the score and a concise comment. Regarding to the comment, it should not only summarize the dialogue's quality but also highlight any issues or shortcomings you may have identified in the dialogue.
+            
+            Below is the dialog:
+            
+            {dialog}  
+            
+            Evaluate the dialog now.
+            """
+        )
+
+        self.quality_chain = LLMChain(llm=ChatOpenAI(temperature=0.2, model_name="gpt-3.5-turbo"), prompt=self.quality_agent_prompt)
+
+    def run_openai_evaluation(self, dialog):
+        res = self.quality_chain.run(dialog=dialog)
+        try:
+            res = json.loads(res)
+        except:
+            res = str(res)
+        return res
+
+    def tod(self):
+        """
+        Evaluate TOD dialogues
+        :return:
+        """
+        folder_name = "Task-Oriented-Dialogues--OpenAI"
+        folder_path = os.path.join(self.data_dir, folder_name)
+        dataset_names = os.listdir(folder_path)
+        print(dataset_names)
+        print()
+        for dataset_name in dataset_names:
+            if not os.path.isdir(os.path.join(folder_path, dataset_name)):
+                continue
+
+            data = open_json(os.path.join(folder_path, dataset_name, "train.json"))
+            f_writer = open(os.path.join(folder_path, dataset_name, "train_quality_scores.json"), "w")
+            print("Start processing: {} #total dialogs: {}".format(dataset_name, len(data)))
+
+            for index, item in enumerate(data):
+
+                output = defaultdict(dict)
+                output["source"] = item["source"]
+                output["quality score"] = self.run_openai_evaluation(item["dialog"])
+
+                json.dump(output, f_writer)
+                f_writer.write("\n")  # Add a new line for readability
+                if index % 10 == 0 or index + 1 == len(data):
+                    f_writer.flush()  # Flush the buffer to update the file immediately
+
+    def run(self):
+        self.tod()
+
+process = EvaluateDialogs()
+# Run evaluations for dialogs
+process.run()

code/preprocess_data_DialSum.py

@@ -0,0 +1,614 @@
+"""
+ Copyright (c) 2023, salesforce.com, inc.
+ All rights reserved.
+ SPDX-License-Identifier: Apache License 2.0
+ For full license text, see the LICENSE file in the repo root or https://www.apache.org/licenses/LICENSE-2.0
+"""
+
+#!/usr/bin/env python3
+#
+import sys, os, pdb
+import json
+import shutil, errno
+from tqdm import tqdm
+import pandas as pd
+from utils.constant import *
+
+
+class PreProcessData(object):
+    """docstring for PreProcessData"""
+    def __init__(self):
+        super(PreProcessData, self).__init__()
+        self.data_dir = "/path/to/where/the/raw/dataset/is"
+        self.save_dir = "/path/to/store/the/processed/dataset/" # e.g. ./data/processed/Dialogue-Summarization
+
+
+    def _load_json(self, path=None):
+        if path is None or not os.path.exists(path):
+            raise IOError('File does not exist: %s' % path)
+            # return None
+        with open(path) as df:
+            data = json.loads(df.read())
+        return data
+
+    
+    def _load_txt(self, path=None, split_tok="\n"):
+        if path is None or not os.path.exists(path):
+            raise IOError('File does not exist: %s' % path)
+        with open(path) as df:
+            data = df.read().strip().split(split_tok)
+        return data
+
+
+    def _load_csv(self, path=None, sep="\t"):
+        if path is None or not os.path.exists(path):
+            raise IOError('File does not exist: %s' % path)
+        with open(path) as df:
+            data = pd.read_csv(df, sep=sep)
+        return data
+
+
+    def _load_jsonl(self, path=None):
+        if path is None or not os.path.exists(path):
+            raise IOError('File does not exist: %s' % path)
+        data = []
+        with open(path) as df:
+            for line in df.readlines():
+                data.append(json.loads(line))
+        return data
+
+
+
+    def _load_dir_json(self, dir_path=None):
+        if dir_path is None or not os.path.exists(dir_path): return None
+        total_data = [] # assume data is a list of dialogs
+        for filename in sorted(os.listdir(dir_path)):
+            if filename in ["schema.json"]: continue
+            if not filename.endswith(".json"): continue
+            file_path = os.path.join(dir_path, filename)
+            data = self._load_json(path=file_path)
+            if type(data) == list:
+                total_data.extend(data)
+            else:
+                total_data.append(data)
+        return total_data
+
+
+    def _load_dir_txt(self, dir_path=None, file_type="txt"):
+        if dir_path is None or not os.path.exists(dir_path): return None
+        total_data = [] # assume data is a list of dialogs
+        for filename in sorted(os.listdir(dir_path)):
+            if not filename.endswith(file_type): continue
+            file_path = os.path.join(dir_path, filename)
+            data = self._load_txt(path=file_path)
+            if type(data) == list:
+                total_data.extend(data)
+            else:
+                total_data.append(data)
+        return total_data
+
+
+    def _load_dir_tsv(self, dir_path=None, sep="\t"):
+        if dir_path is None or not os.path.exists(dir_path): return None
+        total_data = None
+        for filename in sorted(os.listdir(dir_path)):
+            file_path = os.path.join(dir_path, filename)
+            data = self._load_csv(path=file_path, sep=sep)
+            total_data = pd.concat([total_data, data], ignore_index=True)
+        return total_data
+
+
+    def _save_json(self, data, path):
+        with open(path, "w") as tf:
+            json.dump(data, tf, indent=4)
+
+
+    def init_dial(self, dial_idx=0, ori_dial_id=""):
+        dial = {
+            ORI_DIAL_ID: ori_dial_id,
+            DIAL_IDX: dial_idx,
+            ORI_DIAL_INFO: {},
+            LOG: [],
+            PROMPT: [],
+        }
+        return dial
+
+
+    def init_turn(self, turn_id=0, dial_hist=[]):
+        turn = {
+            TURN_ID: turn_id,
+            USR_UTT: "",
+            SYS_UTT: "",
+            DIAL_HIST: " ".join(dial_hist),
+            ORI_USR_ANN: {},
+            ORI_SYS_ANN: {},
+        }
+        return turn
+
+
+    def save_dial(self, data, data_name="", file_idx=0, mode="train"):
+        save_name = f"dialogues_{file_idx}.json"
+        folder_path = os.path.join(self.save_dir, data_name, mode)
+        if not os.path.exists(folder_path): os.makedirs(folder_path)
+        path = os.path.join(folder_path, save_name)
+        self._save_json(data, path)
+
+
+    def copy_general(self, src, dst):
+        try:
+            shutil.copytree(src, dst, dirs_exist_ok=True)
+        except OSError as exc: # python >2.5
+            if exc.errno in (errno.ENOTDIR, errno.EINVAL):
+                shutil.copy(src, dst)
+            else: raise
+
+
+    def copy_related_files(self, data_name, exp_list=[], extra_dir=""):
+        source_dir = os.path.join(self.data_dir, data_name, extra_dir)
+        target_dir = os.path.join(self.save_dir, data_name)
+        for filename in os.listdir(source_dir):
+            if filename.startswith("."): continue # ignore hidden files
+            if filename.startswith("__"): continue # ignore hidden files
+            if filename in exp_list: continue
+            if filename.endswith(".py"): continue
+            source_path = os.path.join(source_dir, filename)
+            target_path = os.path.join(target_dir, filename)
+            self.copy_general(source_path, target_path)
+
+
+    def save_original_examples(self, examples, data_name):
+        """
+        save 5 original data points just for reference and check
+        data would be a list of length 5, each entry is a dialog 
+        in the form of dictionary
+        """
+        path = os.path.join(self.save_dir, data_name, "original_examples.json")
+        self._save_json(examples, path)
+        print("original examples saved")
+
+
+    def save_converted_examples(self, data_name):
+        """
+        extract the first 5 examples from the train set of the 
+        already processed data, just for reference and check
+        """
+        data = self._load_json(os.path.join(self.save_dir, data_name, "train/dialogues_1.json"))
+        examples = {key: data[key] for key in list(data.keys())[:5]}
+        self._save_json(examples, os.path.join(self.save_dir, data_name, "converted_examples.json"))
+        print("converted examples saved")
+
+
+    def _import_system_file(self, filename="", module_name=""):
+        import importlib, sys
+        spec = importlib.util.spec_from_file_location(module_name, filename)
+        module = importlib.util.module_from_spec(spec)
+        sys.modules[module_name] = module
+        spec.loader.exec_module(module)
+        return module
+
+
+    def tweetsum(self):
+        """
+        real data store in kaggle, need to download and preprocess first
+        """
+        data_name = "TweetSumm"
+        # prepare data
+        Modules = self._import_system_file(os.path.join(self.data_dir, data_name, "tweet_sum_processor.py"), "TweetSumProcessor")
+        processor = Modules.TweetSumProcessor(os.path.join(self.data_dir, data_name, "archive/twcs/twcs.csv"))
+        exp_list = ["tweet_sum_data_files", "archive", "tweet_sum_processor.py"]
+        for mode in ["train", "val", "test"]:
+            real_name = f"final_{mode}_tweetsum.jsonl" if mode != "val" else "final_valid_tweetsum.jsonl"
+            path = os.path.join(self.data_dir, data_name, "tweet_sum_data_files", real_name)
+
+            # split = self._load_jsonl(path)
+            new_data = {}
+            file_idx = 1
+            original_data_sample = []
+
+            with open(path) as f:
+                dialog_with_summaries = processor.get_dialog_with_summaries(f.readlines())
+                for dial_idx, dialog_with_summary in tqdm(enumerate(dialog_with_summaries)):
+                    new_dial_id = f"{data_name}--{mode}--{dial_idx+1}"
+
+                    json_format = dialog_with_summary.get_json()
+                    dial = json.loads(json_format)
+                    if mode == "train" and dial_idx < 5:
+                        original_data_sample.append(dial)
+
+                    new_dial = self.init_dial(dial_idx=dial_idx+1, ori_dial_id=dial["dialog"]["dialog_id"]) # idx starts from 1
+                    new_dial[ORI_DIAL_INFO] = {
+                        "summaries" : dial["summaries"]
+                    }
+                    turn_id, dial_hist = 1, []
+                    new_turn = self.init_turn(turn_id=turn_id)
+                    for idx, turn in enumerate(dial["dialog"]["turns"]):
+                        utt = " ".join(turn["sentences"])
+                        if turn["is_agent"]:
+                            new_turn[SYS_UTT] += f" {utt}"
+                            new_turn[SYS_UTT] = new_turn[SYS_UTT].strip()
+                            if idx == len(dial["dialog"]["turns"]) - 1 or \
+                                not dial["dialog"]["turns"][idx+1]["is_agent"]:
+
+                                new_dial[LOG].append(new_turn)
+                                turn_id += 1
+                                if new_turn[USR_UTT]:
+                                    dial_hist.append("<USER> " + new_turn[USR_UTT])
+                                dial_hist.append("<SYSTEM> " + new_turn[SYS_UTT])
+                                new_turn = self.init_turn(turn_id=turn_id)
+                                new_turn[DIAL_HIST] = " ".join(dial_hist)
+                        else:
+                            new_turn[USR_UTT] += f" {utt}"
+                            new_turn[USR_UTT] = new_turn[USR_UTT].strip()
+
+                    new_data[new_dial_id] = new_dial
+                    if (dial_idx+1) % 1000 == 0 or dial_idx+1 == len(dialog_with_summaries):
+                        self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+                        new_data = {} # reset
+                        file_idx += 1
+        
+            if mode == "train": self.save_original_examples(original_data_sample, data_name)
+        self.save_converted_examples(data_name)
+        self.copy_related_files(data_name, exp_list)
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+
+    def samsum(self):
+        """
+        1. achieved from HF datasets "samsum"
+        2. no sys/user, but two human being, assuming the first utterance comes from user, ignore residual
+        """
+        data_name = "SAMSum"
+        # prepare data
+        from datasets import load_dataset
+        data = load_dataset("samsum")
+        for mode in ["train", "val", "test"]:
+            real_name = mode if mode != "val" else "validation"
+            new_data, file_idx = {}, 1
+
+            for dial_idx, dial in tqdm(enumerate(data[real_name])):
+                new_dial_id = f"{data_name}--{mode}--{dial_idx+1}"
+                new_dial = self.init_dial(dial_idx=dial_idx+1, ori_dial_id=dial["id"]) # idx starts from 1
+                new_dial[ORI_DIAL_INFO] = {
+                    "summary" : dial["summary"]
+                }
+                dial_hist = []
+                sep = "\r\n" if "\r\n" in dial["dialogue"] else "\n"
+                for turn_idx, turn in enumerate(dial["dialogue"].split(sep)):
+                    speaker, utt = turn.split(": ")[0], ": ".join(turn.split(": ")[1:])
+                    if turn_idx % 2 == 0:
+                        new_turn = self.init_turn(turn_id=turn_idx//2+1)
+                        new_turn[DIAL_HIST] = " ".join(dial_hist)
+                        new_turn[USR_UTT] = utt.strip().replace("  ", " ")
+                        new_turn[ORI_USR_ANN]['speaker'] = speaker
+                    else:
+                        new_turn[SYS_UTT] = utt.strip().replace("  ", " ")
+                        new_turn[ORI_SYS_ANN]['speaker'] = speaker
+                        dial_hist.append("<USER> " + new_turn[USR_UTT])
+                        dial_hist.append("<SYSTEM> " + new_turn[SYS_UTT])
+                        new_dial[LOG].append(new_turn)
+
+                new_data[new_dial_id] = new_dial
+                if (dial_idx+1) % 1000 == 0 or dial_idx+1 == len(data[real_name]):
+                    self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+                    new_data = {} # reset
+                    file_idx += 1
+        
+        self.save_original_examples(data["train"][:5], data_name)
+        self.save_converted_examples(data_name)
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+
+    def dialogsum(self):
+        """
+        1. we use the data from github: https://github.com/cylnlp/dialogsum/tree/main/DialogSum_Data 
+            but, it is also available from HF datasets "knkarthick/dialogsum"
+        2. no sys/user, but two human being, assuming the first utterance comes from user, ignore residual
+        """
+        data_name = "DialogSum"
+
+        for mode in ["train", "val", "test"]:
+            real_name = mode if mode != "val" else "dev"
+            path = os.path.join(self.data_dir, data_name, f"DialogSum_Data/dialogsum.{real_name}.jsonl")
+            data = self._load_jsonl(path)
+            new_data, file_idx = {}, 1
+
+            for dial_idx, dial in tqdm(enumerate(data)):
+                new_dial_id = f"{data_name}--{mode}--{dial_idx+1}"
+                new_dial = self.init_dial(dial_idx=dial_idx+1, ori_dial_id=dial["fname"]) # idx starts from 1
+                for key in dial:
+                    if key in ["fname", "dialogue"]: continue
+                    new_dial[ORI_DIAL_INFO][key] = dial[key]
+
+                dial_hist = []
+                turns = dial["dialogue"].replace("PErson","Person").split("#Person")[1:]
+                for turn_idx, turn in enumerate(turns):
+                    speaker, utt = turn.split("#:")
+                    speaker = "Person" + speaker
+                    utt = utt.replace("\n","").strip()
+
+                    if turn_idx % 2 == 0:
+                        new_turn = self.init_turn(turn_id=turn_idx//2+1)
+                        new_turn[DIAL_HIST] = " ".join(dial_hist)
+                        new_turn[USR_UTT] = utt.strip()
+                        new_turn[ORI_USR_ANN]['speaker'] = speaker.replace("#","")
+                    else:
+                        new_turn[SYS_UTT] = utt.strip()
+                        new_turn[ORI_SYS_ANN]['speaker'] = speaker.replace("#","")
+                        dial_hist.append("<USER> " + new_turn[USR_UTT])
+                        dial_hist.append("<SYSTEM> " + new_turn[SYS_UTT])
+                        new_dial[LOG].append(new_turn)
+
+                new_data[new_dial_id] = new_dial
+                if (dial_idx+1) % 1000 == 0 or dial_idx+1 == len(data):
+                    self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+                    new_data = {} # reset
+                    file_idx += 1
+        
+            if mode == "train": self.save_original_examples(data[:5], data_name)
+        self.save_converted_examples(data_name)
+        self.copy_related_files(data_name, ['Baseline'])
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+
+    def ami(self):
+        """
+        download processed data from https://drive.google.com/drive/folders/1BbmaZnzG9WrqOO-D3h211NOJePotqwQJ
+        the data is separated into 6 files based on annotation
+        here we extract the dialog context based on file "dialogueActs"
+        no train/val/test split, consider all as train
+        no readme file needs to be copied
+        we use ABCD instead of USR_UTT/SYS_UTT
+
+        1. each dialog contains more than 2 speaker? yes A,B,C,D
+        2. speaking in any order? yes A->B->C->D
+        """
+        data_name = "AMI"
+        mode = "train"
+        data_dir = os.path.join(self.data_dir, data_name, "dialogueActs")
+        new_data, dial_idx = {}, 1
+
+        for filename in os.listdir(data_dir):
+            dial = self._load_json(os.path.join(data_dir, filename))
+            new_dial = self.init_dial(dial_idx=dial_idx) # idx starts from 1
+            # # # save dialog log
+            new_dial[ORI_DIAL_INFO]["dialog history"] = []
+            for turn in dial:
+                new_dial[ORI_DIAL_INFO]["dialog history"].append(turn["speaker"] + " : " + turn["text"])
+
+            # # # save abstractive summary
+            if os.path.exists(os.path.join(self.data_dir, data_name, "abstractive", filename)):
+                abs_sum = self._load_json(os.path.join(self.data_dir, data_name, "abstractive", filename))
+                new_dial[ORI_DIAL_INFO]["abstractive summary"] = abs_sum
+            # # # save extractive summary
+            if os.path.exists(os.path.join(self.data_dir, data_name, "extractive", filename)):
+                ext_sum = self._load_json(os.path.join(self.data_dir, data_name, "extractive", filename))
+                new_dial[ORI_DIAL_INFO]["extractive summary"] = []
+                for ext_turn in ext_sum:
+                    new_dial[ORI_DIAL_INFO]["extractive summary"].append(ext_turn["speaker"] + " : " + ext_turn["text"])
+
+            new_dial_id = f"{data_name}--{mode}--{dial_idx}"
+            new_dial[ORI_DIAL_ID] = filename
+            new_data[new_dial_id] = new_dial
+            dial_idx += 1
+            if dial_idx == 2:
+                self.save_original_examples(dial, data_name)
+
+        self.save_dial(new_data, data_name=data_name, file_idx=1, mode=mode)
+        self.save_converted_examples(data_name)
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+        
+    def icsi(self):
+        """
+        similar as AMI
+        speak can last to A->J
+        """
+        data_name = "ICSI"
+        mode = "train"
+        data_dir = os.path.join(self.data_dir, data_name, "dialogueActs")
+        new_data, dial_idx = {}, 1
+
+        for filename in os.listdir(data_dir):
+            dial = self._load_json(os.path.join(data_dir, filename))
+            new_dial = self.init_dial(dial_idx=dial_idx) # idx starts from 1
+            # # # save dialog log
+            new_dial[ORI_DIAL_INFO]["dialog history"] = []
+            for turn in dial:
+                new_dial[ORI_DIAL_INFO]["dialog history"].append(turn["speaker"] + " : " + turn["text"])
+
+            # # # save abstractive summary
+            if os.path.exists(os.path.join(self.data_dir, data_name, "abstractive", filename)):
+                abs_sum = self._load_json(os.path.join(self.data_dir, data_name, "abstractive", filename))
+                new_dial[ORI_DIAL_INFO]["abstractive summary"] = abs_sum
+            # # # save extractive summary
+            if os.path.exists(os.path.join(self.data_dir, data_name, "extractive", filename)):
+                ext_sum = self._load_json(os.path.join(self.data_dir, data_name, "extractive", filename))
+                new_dial[ORI_DIAL_INFO]["extractive summary"] = []
+                for ext_turn in ext_sum:
+                    new_dial[ORI_DIAL_INFO]["extractive summary"].append(ext_turn["speaker"] + " : " + ext_turn["text"])
+
+            new_dial_id = f"{data_name}--{mode}--{dial_idx}"
+            new_dial[ORI_DIAL_ID] = filename
+            new_data[new_dial_id] = new_dial
+            dial_idx += 1
+            if dial_idx == 2:
+                self.save_original_examples(dial, data_name)
+
+        self.save_dial(new_data, data_name=data_name, file_idx=1, mode=mode)
+        self.save_converted_examples(data_name)
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+
+    def qmsum(self):
+        data_name = "QMSum"
+        for mode in ["train", "val", "test"]:
+            path = os.path.join(self.data_dir, data_name, f"data/ALL/{mode}")
+            data = self._load_dir_json(path)
+            new_data, file_idx = {}, 1
+            for dial_idx, dial in tqdm(enumerate(data)):
+                new_dial_id = f"{data_name}--{mode}--{dial_idx+1}"
+                new_dial = self.init_dial(dial_idx=dial_idx+1)
+                for key_ in dial:
+                    if key_ == "meeting_transcripts": continue
+                    new_dial[ORI_DIAL_INFO][key_] = dial[key_]
+                
+                new_dial[ORI_DIAL_INFO]["dialog history"] = []
+                for turn in dial["meeting_transcripts"]:
+                    new_dial[ORI_DIAL_INFO]["dialog history"].append(turn["speaker"] + " : " + turn["content"])
+
+                new_data[new_dial_id] = new_dial
+                if (dial_idx+1) % 1000 == 0 or dial_idx+1 == len(data):
+                    self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+                    new_data = {} # reset
+                    file_idx += 1
+        
+            if mode == "train": self.save_original_examples(data[:5], data_name)
+        self.save_converted_examples(data_name)
+        self.copy_related_files(data_name, ['Baseline'])
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+
+    def mediasum(self):
+        data_name = "MediaSum"
+        split_id = self._load_json(os.path.join(self.data_dir, data_name, "data/train_val_test_split.json"))
+        data = self._load_json(os.path.join(self.data_dir, data_name, "data/news_dialogue.json"))
+
+        split_id2mode, new_data, file_idx, dial_idx = {}, {}, {}, {}
+        for mode in ["train", "val", "test"]:
+            for dial_id in split_id[mode]:
+                split_id2mode[dial_id] = mode
+            new_data[mode], file_idx[mode], dial_idx[mode] = {}, 1, 1
+
+        for dial in tqdm(data):
+            new_dial = self.init_dial() # idx starts from 1
+            new_dial[ORI_DIAL_ID] = dial['id']
+            for key_ in dial:
+                if key_ in ["id", "utt", "speaker"]: continue
+                new_dial[ORI_DIAL_INFO][key_] = dial[key_]
+            dialog_log = []
+            for idx in range(len(dial["utt"])):
+                dialog_log.append(dial["speaker"][idx] + " : " + dial["utt"][idx])
+            new_dial[ORI_DIAL_INFO]["dialog history"] = dialog_log
+
+            mode = split_id2mode.get(dial["id"], "train")
+            new_dial_id = f"{data_name}--{mode}--{dial_idx[mode]}"
+            new_dial[DIAL_IDX] = dial_idx[mode]
+            new_data[mode][new_dial_id] = new_dial
+            dial_idx[mode] += 1
+
+            if len(new_data[mode]) == 1000:
+                self.save_dial(new_data[mode], data_name=data_name, file_idx=file_idx[mode], mode=mode)
+                new_data[mode] = {} # reset
+                file_idx[mode] += 1
+
+        # if there are some unsaved dialogs left, save it now
+        for mode in ["train", "val", "test"]:
+            if new_data[mode]:
+                self.save_dial(new_data[mode], data_name=data_name, file_idx=file_idx[mode], mode=mode)
+
+        self.save_original_examples(data[:5], data_name)
+        self.save_converted_examples(data_name)
+        self.copy_related_files(data_name, ["data"])
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+
+    def crd3(self):
+        """
+        For this dataset, we choose present only chunk_size=2 offset=0
+        some file are missing for chunk size = 2
+        """
+        data_name = "CRD3"
+        exp_list = []
+        for filename in os.listdir(os.path.join(self.data_dir, data_name)):
+            if filename == "readme.txt": continue
+            if filename == "LICENSE": continue
+            exp_list.append(filename)
+        for mode in ["train", "val", "test"]:
+            new_data, file_idx, dial_idx = {}, 1, 1
+            for file_name in self._load_txt(os.path.join(self.data_dir, data_name, f"data/aligned data/{mode}_files")):
+                file_path = os.path.join(self.data_dir, data_name, f"data/aligned data/c=2/{file_name}_2_0.json")
+                if not os.path.exists(file_path): continue
+                data = self._load_json(file_path)
+
+                new_dial_id = f"{data_name}--{mode}--{dial_idx}"
+                new_dial = self.init_dial(dial_idx=dial_idx)
+                new_dial[ORI_DIAL_ID] = file_name
+                new_dial[ORI_DIAL_INFO] = data
+                new_data[new_dial_id] = new_dial
+                dial_idx += 1
+
+                if (dial_idx) % 1000 == 0:
+                    self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+                    new_data = {} # reset
+                    file_idx += 1
+            if new_data: self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+            if mode == "train": self.save_original_examples([new_dial[ORI_DIAL_INFO]], data_name)
+        self.save_converted_examples(data_name)
+        self.copy_related_files(data_name, exp_list)
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+
+    def ectsum(self):
+        data_name = "ECTSum"
+        for mode in ["train", "val", "test"]:
+            new_data, file_idx, dial_idx = {}, 1, 1
+            data_dir = os.path.join(self.data_dir, data_name, "data/final", mode)
+            for file_name in os.listdir(os.path.join(data_dir, "ects")):
+                if not file_name.endswith("txt"): pdb.set_trace()
+                ect_data = self._load_txt(os.path.join(data_dir, "ects", file_name))
+                sum_data = self._load_txt(os.path.join(data_dir, "gt_summaries", file_name))
+
+                new_dial_id = f"{data_name}--{mode}--{dial_idx}"
+                new_dial = self.init_dial(dial_idx=dial_idx)
+                new_dial[ORI_DIAL_INFO]["file_name"] = file_name
+                new_dial[ORI_DIAL_INFO]["ect"] = ect_data
+                new_dial[ORI_DIAL_INFO]["summary"] = sum_data
+                new_data[new_dial_id] = new_dial
+                dial_idx += 1
+
+                if (dial_idx) % 1000 == 0:
+                    self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+                    new_data = {} # reset
+                    file_idx += 1
+            if new_data: self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+            if mode == "train": self.save_original_examples([new_dial[ORI_DIAL_INFO]], data_name)
+        self.save_converted_examples(data_name)
+        self.copy_related_files(data_name, ['codes', 'data'])
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+
+    def run_all(self):
+        # self.todsum()
+        # self.tweetsum()
+        # self.samsum()
+        # self.dialogsum()
+        # self.ami()
+        # self.icsi()
+        # self.qmsum()
+        self.mediasum()
+        # self.crd3()
+        # self.ectsum()
+        pass
+
+
+    def copy_example(self):
+        source_dir = self.save_dir
+        target_dir = "/home/qkun/projs/TOD-Project/Datasets/Dialogue-Summarization_PROCESSED/"
+        file_list = ["converted_examples.json", "original_examples.json", "readme.txt", "LICENSE"]
+        for dir_name in sorted(os.listdir(source_dir)):
+            if os.path.isfile(os.path.join(source_dir, dir_name)): continue
+            if not os.path.exists(os.path.join(target_dir, dir_name)): os.makedirs(os.path.join(target_dir, dir_name))
+            for filename in file_list:
+                source_path = os.path.join(source_dir, dir_name, filename)
+                target_path = os.path.join(target_dir, dir_name, filename)
+                if not os.path.exists(source_path): continue
+                shutil.copy(source_path, target_path)
+
+
+def main():
+    preprocess = PreProcessData()
+    preprocess.run_all()
+    preprocess.copy_example()
+
+if __name__ == '__main__':
+    main()

code/preprocess_data_KG.py

@@ -0,0 +1,368 @@
+"""
+ Copyright (c) 2023, salesforce.com, inc.
+ All rights reserved.
+ SPDX-License-Identifier: Apache License 2.0
+ For full license text, see the LICENSE file in the repo root or https://www.apache.org/licenses/LICENSE-2.0
+"""
+
+#!/usr/bin/env python3
+#
+import sys, os, pdb
+import json
+import shutil, errno
+from tqdm import tqdm
+import pandas as pd
+from utils.constant import *
+
+
+class PreProcessData(object):
+    """docstring for PreProcessData"""
+    def __init__(self):
+        super(PreProcessData, self).__init__()
+        self.data_dir = "/path/to/where/the/raw/dataset/is"
+        self.save_dir = "/path/to/store/the/processed/dataset/" # e.g. ./data/processed/Knowledge-Grounded
+
+
+    def _load_json(self, path=None):
+        if path is None or not os.path.exists(path):
+            raise IOError('File does not exist: %s' % path)
+            # return None
+        with open(path) as df:
+            data = json.loads(df.read())
+        return data
+
+    
+    def _load_txt(self, path=None, split_tok="\n"):
+        if path is None or not os.path.exists(path):
+            raise IOError('File does not exist: %s' % path)
+        with open(path) as df:
+            data = df.read().strip().split(split_tok)
+        return data
+
+
+    def _load_csv(self, path=None, sep="\t"):
+        if path is None or not os.path.exists(path):
+            raise IOError('File does not exist: %s' % path)
+        with open(path) as df:
+            data = pd.read_csv(df, sep=sep)
+        return data
+
+
+    def _load_jsonl(self, path=None):
+        if path is None or not os.path.exists(path):
+            raise IOError('File does not exist: %s' % path)
+        data = []
+        with open(path) as df:
+            for line in df.readlines():
+                data.append(json.loads(line))
+        return data
+
+
+
+    def _load_dir_json(self, dir_path=None):
+        if dir_path is None or not os.path.exists(dir_path): return None
+        total_data = [] # assume data is a list of dialogs
+        for filename in sorted(os.listdir(dir_path)):
+            if filename in ["schema.json"]: continue
+            if not filename.endswith(".json"): continue
+            file_path = os.path.join(dir_path, filename)
+            data = self._load_json(path=file_path)
+            if type(data) == list:
+                total_data.extend(data)
+            else:
+                total_data.append(data)
+        return total_data
+
+
+    def _load_dir_txt(self, dir_path=None, file_type="txt"):
+        if dir_path is None or not os.path.exists(dir_path): return None
+        total_data = [] # assume data is a list of dialogs
+        for filename in sorted(os.listdir(dir_path)):
+            if not filename.endswith(file_type): continue
+            file_path = os.path.join(dir_path, filename)
+            data = self._load_txt(path=file_path)
+            if type(data) == list:
+                total_data.extend(data)
+            else:
+                total_data.append(data)
+        return total_data
+
+
+    def _load_dir_tsv(self, dir_path=None, sep="\t"):
+        if dir_path is None or not os.path.exists(dir_path): return None
+        total_data = None
+        for filename in sorted(os.listdir(dir_path)):
+            file_path = os.path.join(dir_path, filename)
+            data = self._load_csv(path=file_path, sep=sep)
+            total_data = pd.concat([total_data, data], ignore_index=True)
+        return total_data
+
+
+    def _save_json(self, data, path):
+        with open(path, "w") as tf:
+            json.dump(data, tf, indent=4)
+
+
+    def init_dial(self, dial_idx=0, ori_dial_id=""):
+        dial = {
+            ORI_DIAL_ID: "",
+            DIAL_IDX: dial_idx,
+            ORI_DIAL_INFO: {},
+            LOG: [],
+            # EK_ORI: {
+            #     TOD_EK:{},
+            # },
+            # EK: "",
+            PROMPT: [],
+        }
+        return dial
+
+
+    def init_turn(self, turn_id=0, dial_hist=[]):
+        turn = {
+            TURN_ID: int(turn_id),
+            USR_UTT: "",
+            SYS_UTT: "",
+            DIAL_HIST: " ".join(dial_hist),
+            ORI_USR_ANN: {},
+            ORI_SYS_ANN: {},
+            EK_ORI: {
+                TOD_EK:{},
+            },
+            EK: "",
+        }
+        return turn
+
+
+    def save_dial(self, data, data_name="", file_idx=0, mode="train"):
+        save_name = f"dialogues_{file_idx}.json"
+        folder_path = os.path.join(self.save_dir, data_name, mode)
+        if not os.path.exists(folder_path): os.makedirs(folder_path)
+        path = os.path.join(folder_path, save_name)
+        self._save_json(data, path)
+
+
+    def save_original_examples(self, examples, data_name):
+        """
+        save 5 original data points just for reference and check
+        data would be a list of length 5, each entry is a dialog 
+        in the form of dictionary
+        """
+        path = os.path.join(self.save_dir, data_name, "original_examples.json")
+        self._save_json(examples, path)
+        print("original examples saved")
+
+
+    def save_converted_examples(self, data_name):
+        """
+        extract the first 5 examples from the train set of the 
+        already processed data, just for reference and check
+        """
+        data = self._load_json(os.path.join(self.save_dir, data_name, "train/dialogues_1.json"))
+        examples = {key: data[key] for key in list(data.keys())[:5]}
+        self._save_json(examples, os.path.join(self.save_dir, data_name, "converted_examples.json"))
+        print("converted examples saved")
+
+
+    def dict_to_str(self, ek_ori):
+        """
+        turn non-flat external knowledge into string
+        original format:
+            "metadata":{
+                domain: [
+                    {
+                        attr1: value1,
+                        attr2: value2,
+                        ...
+                    },
+                    ...
+                ]
+            }
+        output format:
+            ( metadata : ( domain : ( attr1 : value1 | attr2 : value2 | ... ) | ( ... ) | ... ))
+        """
+        ek = str(ek_ori).replace("'"," ").replace(", "," | ")
+        ek = ek.replace("{","(").replace("}",")").replace("[","(").replace("]",")")
+        ek = ek.replace("  ", " ")
+        return ek
+
+
+    def wow(self):
+        """
+        Speakers: Apprentice (always starts a turn), Wizard (ends a turn)
+        turn-level EK only
+        checked facts:
+
+        """
+        data_name = "wizard_of_wikipedia"
+        for mode in ["train", "val", "test"]:
+            if mode == "train": filename = "train.json"
+            elif mode == "val": filename = "valid_topic_split.json"
+            else:               filename = "test_topic_split.json"
+            data = self._load_json(os.path.join(self.data_dir, data_name, filename))
+            new_data, file_idx = {}, 1
+            for dial_idx, dial in tqdm(enumerate(data)):
+                new_dial = self.init_dial(dial_idx=dial_idx+1)
+                new_dial_id = f"{data_name}--{mode}--{dial_idx+1}"
+                new_dial[ORI_DIAL_INFO]["chosen_topic"] = dial["chosen_topic"]
+                new_dial[ORI_DIAL_INFO]["persona"] = dial["persona"]
+                new_dial[ORI_DIAL_INFO]["wizard_eval"] = dial["wizard_eval"]
+                new_dial[ORI_DIAL_INFO]["chosen_topic_passage"] = dial["chosen_topic_passage"]
+                turn_idx, dial_hist = 1, []
+                new_turn = self.init_turn(turn_id=turn_idx)
+                for turn in (dial["dialog"]):
+                    if turn["speaker"].split("_")[-1] == "Apprentice":
+                        new_turn = self.init_turn(turn_id=turn_idx)
+                        new_turn[DIAL_HIST] = " ".join(dial_hist)
+                        for key_ in turn:
+                            if key_ == "text":
+                                new_turn[USR_UTT] = turn["text"]
+                            else:
+                                new_turn[ORI_USR_ANN][key_] = turn[key_]
+
+                        dial_hist.append(f"<{SPEAKER1.upper()}> " + new_turn[USR_UTT])
+                    elif turn["speaker"].split("_")[-1] == "Wizard":
+                        for key_ in turn:
+                            if key_ == "text":
+                                new_turn[SYS_UTT] = turn["text"]
+                            else:
+                                new_turn[ORI_SYS_ANN][key_] = turn[key_]
+                        dial_hist.append(f"<{SPEAKER2.upper()}> " + new_turn[SYS_UTT])
+                        if not turn["checked_passage"]:
+                            turn["checked_passage"] = {"none": dial["chosen_topic"]}
+                        if not turn["checked_sentence"]:
+                            turn["checked_sentence"] = {"no_passages_used": "no_passages_used"}
+                        if len(turn["checked_passage"]) == 2 and "no_passages_used" in turn["checked_passage"]: 
+                            # for case  turn["checked_passage"] = {'chosen_topic_0_Aquarium': 'Aquarium', 'no_passages_used': 'no_passages_used'}
+                            del turn["checked_passage"]["no_passages_used"]
+                        # if len(turn["checked_passage"].values()) != 1 or len(turn["checked_sentence"].values()) != 1: pdb.set_trace()
+                        title = list(turn["checked_passage"].values())[0]
+                        sent = list(turn["checked_sentence"].values())[0]
+                        new_turn[EK_ORI][TOD_EK][title] = sent
+                        new_turn[EK] = self.dict_to_str(new_turn[EK_ORI][TOD_EK])
+                        new_dial[LOG].append(new_turn)
+                        turn_idx += 1
+                    else:
+                        print(turn["speaker"])
+                        raise ValueError("Unknown speaker")
+
+                if not new_turn[SYS_UTT]:
+                    new_dial[LOG].append(new_turn)
+
+                new_data[new_dial_id] = new_dial
+                if new_dial[DIAL_IDX] % 10000 == 0:
+                    self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+                    new_data = {} # reset
+                    file_idx += 1
+            if new_data: self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+            if mode == "train": self.save_original_examples(data[:5], data_name)
+            print(f"finishing processing {dial_idx+1} dialogs for {mode} set ...")
+        self.save_converted_examples(data_name)
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+                
+
+    def woi(self):
+        """
+        actions:
+            Apprentice => Wizard
+            Wizard => SearchAgent
+            SearchAgent => Wizard
+            Wizard => Apprentice
+        """
+        data_name = "wizard_of_internet"
+        for mode in ["test", "train"]:
+            data = self._load_jsonl(os.path.join(self.data_dir, data_name, f"{mode}.jsonl"))
+            data = {k:v for dial in data for k,v in dial.items()}
+            new_data, file_idx, dial_idx = {}, 1, 1
+            for dial_id, dial in tqdm(data.items()):
+                # new_dial = dial
+                new_dial = self.init_dial(dial_idx=dial_idx)
+                new_dial_id = f"{data_name}--{mode}--{dial_idx}"
+                new_dial[ORI_DIAL_ID] = dial_id
+                new_dial[ORI_DIAL_INFO]["apprentice_persona"] = dial["apprentice_persona"]
+                new_dial[ORI_DIAL_INFO]["start_timestamp"] = dial["start_timestamp"]
+                turn_idx, dial_hist = 1, []
+                new_turn = self.init_turn(turn_id=turn_idx)
+                for turn in dial["dialog_history"]:
+                    if turn["action"] == "Apprentice => Wizard":
+                        new_turn = self.init_turn(turn_id=turn_idx)
+                        new_turn[DIAL_HIST] = " ".join(dial_hist)
+                        new_turn[USR_UTT] = turn["text"]
+                        new_turn[ORI_USR_ANN]["timestamp"] = turn["timestamp"]
+                        dial_hist.append(f"<{SPEAKER1.upper()}> " + new_turn[USR_UTT])
+                    elif turn["action"] == "Wizard => SearchAgent":
+                        if "query" not in new_turn[ORI_SYS_ANN]:
+                            new_turn[ORI_SYS_ANN]["query"] = []
+                        new_turn[ORI_SYS_ANN]["query"].append({
+                            "query": turn["text"],
+                            "query_result": "",
+                            "timestamp_query": turn["timestamp"],
+                        })
+                    elif turn["action"] == "SearchAgent => Wizard":
+                        # checked, each query corresponds to one query result
+                        # if new_turn[ORI_SYS_ANN]["query"][-1]["query_result"]: pdb.set_trace()
+                        new_turn[ORI_SYS_ANN]["query"][-1]["query_result"] = turn["context"]
+                    elif turn["action"] == "Wizard => Apprentice":
+                        new_turn[SYS_UTT] = turn["text"]
+                        for doc_id, doc in enumerate(turn["context"]["selected_contents"][1:]):
+                            for sent_id, choose in enumerate(doc):
+                                if choose:
+                                    title = turn["context"]["contents"][doc_id]["title"]
+                                    sent  = turn["context"]["contents"][doc_id]["content"][sent_id]
+                                    if title not in new_turn[EK_ORI][TOD_EK]:
+                                        new_turn[EK_ORI][TOD_EK][title] = []
+                                    new_turn[EK_ORI][TOD_EK][title].append(sent)
+                        new_turn[EK] = self.dict_to_str(new_turn[EK_ORI][TOD_EK])
+                        new_turn[ORI_SYS_ANN]["context"] = turn["context"]
+                        new_turn[ORI_SYS_ANN]["timestamp"] = turn["timestamp"]
+                        dial_hist.append(f"<{SPEAKER2.upper()}> " + new_turn[SYS_UTT])
+                        new_dial[LOG].append(new_turn)
+                        turn_idx += 1
+                    else:
+                        # checked, no such turns
+                        print(turn["action"])
+                        raise ValueError("The fifth case")
+                if not new_turn[SYS_UTT]:
+                    new_dial[LOG].append(new_turn)
+                
+                # new_dial[EK_ORI][TOD_EK]["apprentice_persona"] = dial["apprentice_persona"]
+                # new_dial[EK] = self.dict_to_str(new_dial[EK_ORI][TOD_EK])
+                new_data[new_dial_id] = new_dial
+                if dial_idx % 10000 == 0:
+                    self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+                    new_data = {} # reset
+                    file_idx += 1
+                dial_idx += 1
+            if new_data: self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+            if mode == "train": self.save_original_examples({k:data[k] for k in list(data.keys())[:5]}, data_name)
+            print(f"finishing processing {dial_idx-1} dialogs for {mode} set ...")
+        self.save_converted_examples(data_name)
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+    def run_all(self):
+        self.wow()
+        self.woi()
+
+
+    def copy_example(self):
+        source_dir = self.save_dir
+        for target_dir in [ "/home/qkun/projs/TOD-Project/Datasets/Knowledge-Grounded_PROCESSED/", "/home/qkun/projs/DialogStudio-Release/knowledge-grounded-dialogues/"]:
+            # target_dir = "/home/qkun/projs/TOD-Project/Datasets/Knowledge-Grounded_PROCESSED/"
+            file_list = ["converted_examples.json", "original_examples.json", "readme.txt", "LICENSE"]
+            for dir_name in sorted(os.listdir(source_dir)):
+                if os.path.isfile(os.path.join(source_dir, dir_name)): continue
+                if not os.path.exists(os.path.join(target_dir, dir_name)): os.makedirs(os.path.join(target_dir, dir_name))
+                for filename in file_list:
+                    source_path = os.path.join(source_dir, dir_name, filename)
+                    target_path = os.path.join(target_dir, dir_name, filename)
+                    if not os.path.exists(source_path): continue
+                    shutil.copy(source_path, target_path)
+
+
+def main():
+    preprocess = PreProcessData()
+    preprocess.run_all()
+    preprocess.copy_example()
+
+if __name__ == '__main__':
+    main()

code/preprocess_data_OD.py

@@ -0,0 +1,574 @@
+"""
+ Copyright (c) 2023, salesforce.com, inc.
+ All rights reserved.
+ SPDX-License-Identifier: Apache License 2.0
+ For full license text, see the LICENSE file in the repo root or https://www.apache.org/licenses/LICENSE-2.0
+"""
+
+#!/usr/bin/env python3
+#
+import sys, os, pdb
+import json
+import shutil, errno
+from tqdm import tqdm
+import pandas as pd
+from constant import *
+
+
+class PreProcessData(object):
+    """docstring for PreProcessData"""
+    def __init__(self):
+        super(PreProcessData, self).__init__()
+        self.data_dir = "/path/to/where/the/raw/dataset/is"
+        self.save_dir = "/path/to/store/the/processed/dataset/" # e.g. ./data/processed/Open-Domain
+
+
+    def _load_json(self, path=None):
+        if path is None or not os.path.exists(path):
+            raise IOError('File does not exist: %s' % path)
+            # return None
+        with open(path) as df:
+            data = json.loads(df.read())
+        return data
+
+    
+    def _load_txt(self, path=None, split_tok="\n", encoding="utf-8"):
+        if path is None or not os.path.exists(path):
+            raise IOError('File does not exist: %s' % path)
+        with open(path, 'r', encoding=encoding) as df:
+            data = df.read().strip().split(split_tok)
+        return data
+
+
+    def _load_csv(self, path=None, sep="\t"):
+        if path is None or not os.path.exists(path):
+            raise IOError('File does not exist: %s' % path)
+        with open(path) as df:
+            data = pd.read_csv(df, sep=sep)
+        return data
+
+
+    def _load_jsonl(self, path=None):
+        if path is None or not os.path.exists(path):
+            raise IOError('File does not exist: %s' % path)
+        data = []
+        with open(path) as df:
+            for line in df.readlines():
+                data.append(json.loads(line))
+        return data
+
+
+
+    def _load_dir_json(self, dir_path=None):
+        if dir_path is None or not os.path.exists(dir_path): return None
+        total_data = [] # assume data is a list of dialogs
+        for filename in sorted(os.listdir(dir_path)):
+            if filename in ["schema.json"]: continue
+            if not filename.endswith(".json"): continue
+            file_path = os.path.join(dir_path, filename)
+            data = self._load_json(path=file_path)
+            if type(data) == list:
+                total_data.extend(data)
+            else:
+                total_data.append(data)
+        return total_data
+
+
+    def _load_dir_txt(self, dir_path=None, file_type="txt"):
+        if dir_path is None or not os.path.exists(dir_path): return None
+        total_data = [] # assume data is a list of dialogs
+        for filename in sorted(os.listdir(dir_path)):
+            if not filename.endswith(file_type): continue
+            file_path = os.path.join(dir_path, filename)
+            data = self._load_txt(path=file_path)
+            if type(data) == list:
+                total_data.extend(data)
+            else:
+                total_data.append(data)
+        return total_data
+
+
+    def _load_dir_tsv(self, dir_path=None, sep="\t"):
+        if dir_path is None or not os.path.exists(dir_path): return None
+        total_data = None
+        for filename in sorted(os.listdir(dir_path)):
+            file_path = os.path.join(dir_path, filename)
+            data = self._load_csv(path=file_path, sep=sep)
+            total_data = pd.concat([total_data, data], ignore_index=True)
+        return total_data
+
+
+    def _save_json(self, data, path):
+        with open(path, "w") as tf:
+            json.dump(data, tf, indent=4)
+
+
+    def init_dial(self, dial_idx=0, ori_dial_id=""):
+        dial = {
+            ORI_DIAL_ID: ori_dial_id,
+            DIAL_IDX: int(dial_idx),
+            ORI_DIAL_INFO: {},
+            LOG: [],
+            PROMPT: [],
+        }
+        return dial
+
+
+    def init_turn(self, turn_id=0, dial_hist=[]):
+        turn = {
+            TURN_ID: int(turn_id),
+            USR_UTT: "",
+            SYS_UTT: "",
+            DIAL_HIST: " ".join(dial_hist),
+            ORI_USR_ANN: {},
+            ORI_SYS_ANN: {},
+        }
+        return turn
+
+
+    def save_dial(self, data, data_name="", file_idx=0, mode="train"):
+        save_name = f"dialogues_{file_idx}.json"
+        folder_path = os.path.join(self.save_dir, data_name, mode)
+        if not os.path.exists(folder_path): os.makedirs(folder_path)
+        path = os.path.join(folder_path, save_name)
+        self._save_json(data, path)
+
+
+    def save_original_examples(self, examples, data_name):
+        """
+        save 5 original data points just for reference and check
+        data would be a list of length 5, each entry is a dialog 
+        in the form of dictionary
+        """
+        path = os.path.join(self.save_dir, data_name, "original_examples.json")
+        self._save_json(examples, path)
+        print("original examples saved")
+
+
+    def save_converted_examples(self, data_name):
+        """
+        extract the first 5 examples from the train set of the 
+        already processed data, just for reference and check
+        """
+        data = self._load_json(os.path.join(self.save_dir, data_name, "train/dialogues_1.json"))
+        examples = {key: data[key] for key in list(data.keys())[:5]}
+        self._save_json(examples, os.path.join(self.save_dir, data_name, "converted_examples.json"))
+        print("converted examples saved")
+
+
+
+    def places(self):
+        """
+        no train/val/test split"""
+        data_name = "PLACES3.5"
+        mode = "train"
+        data = self._load_jsonl(os.path.join(self.data_dir, data_name, "data.jsonl"))
+        new_data, file_idx, dial_idx = {}, 1, 1
+        for dial in (data):
+            new_dial = self.init_dial(dial_idx=dial_idx)
+            new_dial_id = f"{data_name}--{mode}--{dial_idx}"
+            for key in dial:
+                if key == "conversation": continue
+                new_dial[ORI_DIAL_INFO][key] = dial[key]
+            dial_hist, multiparty = [], False
+            for turn_idx, utt in enumerate(dial["conversation"]):
+                if utt.startswith("Alice:"):
+                    new_turn = self.init_turn(turn_id=turn_idx//2+1)
+                    new_turn[DIAL_HIST] = " ".join(dial_hist)
+                    new_turn[USR_UTT] = utt.split("Alice:")[-1].strip()
+                    dial_hist.append(f"<{SPEAKER1.upper()}> " + new_turn[USR_UTT])
+                elif utt.startswith("Bob:"):
+                    new_turn[SYS_UTT] = utt.split("Bob:")[-1].strip()
+                    dial_hist.append(f"<{SPEAKER2.upper()}> " + new_turn[SYS_UTT])
+                    new_dial[LOG].append(new_turn)
+                elif utt.startswith("Emilie:"):
+                    multiparty = True
+                    break
+                else:
+                    if len(utt.split(":")[0].split()) == 1:
+                        # might have a third speaker
+                        raise ValueError("Unknown Speaker ... ")
+                    else:
+                        if not turn_idx: continue
+                        if new_turn[SYS_UTT]:
+                            new_turn[SYS_UTT] += " " + utt
+                        else:
+                            new_turn[USR_UTT] += " " + utt
+                        dial_hist[-1] += " " + utt
+            if multiparty: continue
+            new_data[new_dial_id] = new_dial
+            if (dial_idx) % 10000 == 0:
+                self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+                new_data = {} # reset
+                file_idx += 1
+            dial_idx += 1
+        if new_data: self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+        print(f"finishing processing {new_dial[DIAL_IDX]} dialogs for {mode} set ...")
+        self.save_original_examples(data[:5], data_name)
+        self.save_converted_examples(data_name)
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+
+    def chitchat(self):
+        """
+        no train/val/test split"""
+        data_name = "chitchat-dataset"
+        mode = "train"
+        data = self._load_json(os.path.join(self.data_dir, data_name, "chitchat_dataset/dataset.json"))
+        new_data, file_idx, dial_idx = {}, 1, 1
+        for dial_id, dial in data.items():
+            new_dial = self.init_dial(dial_idx=dial_idx)
+            new_dial_id = f"{data_name}--{mode}--{dial_idx}"
+            new_dial[ORI_DIAL_ID] = dial_id
+            for key in dial:
+                if key == "messages": continue
+                new_dial[ORI_DIAL_INFO][key] = dial[key]
+            dial_hist, speakers = [], []
+            for turn in dial["messages"]:
+                if turn[0]["sender"] not in speakers:
+                    speakers.append(turn[0]["sender"])
+            if len(speakers) < 2: continue
+            # if len(speakers) != 2:
+            #     print("This is a multi-party dialog")
+            #     continue
+            for turn_idx, turn in enumerate(dial["messages"]):
+                if turn[0]["sender"] == speakers[0]:
+                    new_turn = self.init_turn(turn_id=turn_idx//2+1)
+                    new_turn[DIAL_HIST] = " ".join(dial_hist)
+                    new_turn[USR_UTT] = " ".join([row["text"] for row in turn])
+                    new_turn[ORI_USR_ANN]["sender"] = turn[0]["sender"]
+                    new_turn[ORI_USR_ANN]["timestamp"] = [row["timestamp"] for row in turn]
+                    dial_hist.append(f"<{SPEAKER1.upper()}> " + new_turn[USR_UTT])
+
+                elif turn[0]["sender"] == speakers[1]:
+                    new_turn[SYS_UTT] = " ".join([row["text"] for row in turn])
+                    new_turn[ORI_SYS_ANN]["sender"] = turn[0]["sender"]
+                    new_turn[ORI_SYS_ANN]["timestamp"] = [row["timestamp"] for row in turn]
+                    dial_hist.append(f"<{SPEAKER2.upper()}> " + new_turn[SYS_UTT])
+                    new_dial[LOG].append(new_turn)
+                    
+            new_data[new_dial_id] = new_dial
+            if (dial_idx) % 10000 == 0:
+                self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+                new_data = {} # reset
+                file_idx += 1
+            dial_idx += 1
+        if new_data: self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+        print(f"finishing processing {new_dial[DIAL_IDX]} dialogs for {mode} set ...")
+        self.save_original_examples({k:data[k] for k in list(data.keys())[:5]}, data_name)
+        self.save_converted_examples(data_name)
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+        
+
+    def prosocial(self):
+        data_name = "Prosocial"
+        from datasets import load_dataset
+        for mode in ["train", "val", "test"]:
+            new_data, file_idx = {}, 1
+            real_name = "validation" if mode == "val" else mode
+            data = load_dataset("allenai/prosocial-dialog", split=real_name)
+            data_df = data.to_pandas()
+            for row_id in (range(len(data_df))):
+                if data_df["response_id"][row_id] == 0:
+                    new_dial = self.init_dial(dial_idx=data_df["dialogue_id"][row_id]+1)
+                    dial_hist = []
+
+                new_turn = self.init_turn(turn_id=data_df["response_id"][row_id]+1)
+                new_turn[DIAL_HIST] = " ".join(dial_hist)
+                new_turn[USR_UTT] = data_df["context"][row_id]
+                new_turn[SYS_UTT] = data_df["response"][row_id]
+                dial_hist.append(f"<{SPEAKER1.upper()}> " + new_turn[USR_UTT])
+                dial_hist.append(f"<{SPEAKER2.upper()}> " + new_turn[SYS_UTT])
+
+                for key in data_df.keys():
+                    if key in ["context", "response"]: continue
+                    # numpy.ndarray cannot be written into json
+                    if type(data_df[key][row_id]) == str:
+                        new_turn[ORI_USR_ANN][key] = data_df[key][row_id]
+                    else:
+                        new_turn[ORI_USR_ANN][key] = data_df[key][row_id].tolist()
+
+                new_dial[LOG].append(new_turn)
+                if data_df["episode_done"][row_id]:
+                    new_dial_id = f"{data_name}--{mode}--{new_dial[DIAL_IDX]}"
+                    new_data[new_dial_id] = new_dial
+                    if new_dial[DIAL_IDX] % 10000 == 0:
+                        self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+                        new_data = {} # reset
+                        file_idx += 1
+            if new_data: self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+            print(f"finishing processing {new_dial[DIAL_IDX]} dialogs for {mode} set ...")
+        self.save_original_examples(data[:5], data_name)
+        self.save_converted_examples(data_name)
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+
+    def hhrlhf(self):
+        """
+        only use the chosen pair"""
+        from datasets import load_dataset
+        data_name = "HH-RLHF"
+        for mode in ["train", "test"]:
+            data = load_dataset("Anthropic/hh-rlhf", split=mode)
+            data_df = data.to_pandas()
+            new_data, file_idx = {}, 1
+            for i in (range(len(data_df))):
+                new_dial = self.init_dial(dial_idx=i+1)
+                new_dial_id = f"{data_name}--{mode}--{i+1}"
+                dial_hist = []
+                utts = data_df["chosen"][i].replace("Assistant:", "Human:").split("Human:")
+                for turn_idx, utt in enumerate(utts[1:]):
+                    utt = utt.replace("\n\n", " ").strip()
+                    if turn_idx % 2 == 0:
+                        new_turn = self.init_turn(turn_id=turn_idx//2+1)
+                        new_turn[DIAL_HIST] = " ".join(dial_hist)
+                        new_turn[USR_UTT] = utt
+                        dial_hist.append(f"<{SPEAKER1.upper()}> " + new_turn[USR_UTT])
+                    else:
+                        new_turn[SYS_UTT] = utt
+                        dial_hist.append(f"<{SPEAKER2.upper()}> " + new_turn[SYS_UTT])
+                        new_dial[LOG].append(new_turn)
+                    
+                new_data[new_dial_id] = new_dial
+                if new_dial[DIAL_IDX] % 10000 == 0:
+                    self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+                    new_data = {} # reset
+                    file_idx += 1
+            if new_data: self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+            print(f"finishing processing {new_dial[DIAL_IDX]} dialogs for {mode} set ...")
+        self.save_original_examples(data[:5], data_name)
+        self.save_converted_examples(data_name)
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+
+    def empathetic(self):
+        """
+        consecutive turns from the same speaker happens"""
+        data_name = "Empathetic"
+        from datasets import load_dataset
+        for mode in ["train", "val", "test"]:
+            real_name = "validation" if mode == "val" else mode
+            data = load_dataset("empathetic_dialogues", split=real_name)
+            data_df = data.to_pandas()
+            new_data, file_idx, dial_idx, speakers = {}, 1, 1, []
+            for row_id in (range(len(data_df))):
+                utt = data_df["utterance"][row_id].replace("_comma_", ",").strip()
+                if data_df["utterance_idx"][row_id] == 1:
+                    new_dial = self.init_dial(dial_idx)
+                    new_dial[ORI_DIAL_ID] = data_df["conv_id"][row_id]
+                    new_dial[ORI_DIAL_INFO]["context"] = data_df["context"][row_id]
+                    new_dial[ORI_DIAL_INFO]["selfeval"] = data_df["selfeval"][row_id]
+                    dial_hist = []
+
+                    # process the first turn
+                    new_turn = self.init_turn(turn_id=1)
+                    new_turn[USR_UTT] = data_df["prompt"][row_id].strip()
+                    new_turn[SYS_UTT] = utt
+                    new_turn[ORI_USR_ANN]["tags"] = ""
+                    new_turn[ORI_USR_ANN]["speaker_idx"] = int(data_df["speaker_idx"][row_id+1])
+                    new_turn[ORI_SYS_ANN]["tags"] = data_df["tags"][row_id]
+                    new_turn[ORI_SYS_ANN]["speaker_idx"] = int(data_df["speaker_idx"][row_id])
+
+                    dial_hist.append(f"<{SPEAKER1.upper()}> " + new_turn[USR_UTT])
+                    dial_hist.append(f"<{SPEAKER2.upper()}> " + new_turn[SYS_UTT])
+                    # speakers.append(data_df["speaker_idx"][row_id])
+                    # in the first turn, the first speaker's utt is in the prompt and 
+                    # utterance contains the utt from the second speaker
+                    second_speaker_id = data_df["speaker_idx"][row_id]
+                    new_dial[LOG].append(new_turn)
+                    new_turn = self.init_turn(turn_id=(int(data_df["utterance_idx"][row_id])+1)//2+1)
+                    new_turn[DIAL_HIST] = " ".join(dial_hist)
+                
+                elif data_df["speaker_idx"][row_id] == second_speaker_id:
+                    if not new_turn[USR_UTT]: # in this case, consecutive turns from system side happens, we add utt directly to new_dial[LOG][-1]
+                        new_dial[LOG][-1][SYS_UTT] += " " + utt
+                        dial_hist[-1] += " " + utt
+                        new_turn[DIAL_HIST] = " ".join(dial_hist)
+                    else:
+                        new_turn[SYS_UTT] = utt
+                        new_turn[ORI_SYS_ANN]["tags"] = data_df["tags"][row_id]
+                        new_turn[ORI_SYS_ANN]["speaker_idx"] = int(data_df["speaker_idx"][row_id])
+                        dial_hist.append(f"<{SPEAKER2.upper()}> " + new_turn[SYS_UTT])
+                        new_dial[LOG].append(new_turn)
+                        new_turn = self.init_turn(turn_id=(int(data_df["utterance_idx"][row_id])+1)//2+1)
+                        new_turn[DIAL_HIST] = " ".join(dial_hist)
+
+                else:
+                    if not new_turn[USR_UTT]:
+                        new_turn[USR_UTT] = utt
+                        new_turn[ORI_USR_ANN]["tags"] = data_df["tags"][row_id]
+                        new_turn[ORI_USR_ANN]["speaker_idx"] = int(data_df["speaker_idx"][row_id])
+                        dial_hist.append(f"<{SPEAKER1.upper()}> " + new_turn[USR_UTT])
+                    else: # in this case, consecutive turns from user side happens, we add utt directly to new_turn
+                        new_turn[USR_UTT] += " " + utt
+                        dial_hist[-1] += " " + utt
+
+                if row_id == len(data_df)-1 or data_df["utterance_idx"][row_id+1] == 1:
+                    # append the rest dialog in case ends with user side
+                    if new_turn[USR_UTT]:
+                        new_dial[LOG].append(new_turn)
+
+                    new_dial_id = f"{data_name}--{mode}--{dial_idx}"
+                    new_data[new_dial_id] = new_dial
+                    
+                    if dial_idx % 10000 == 0:
+                        self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+                        new_data = {} # reset
+                        file_idx += 1
+                    dial_idx += 1
+            if new_data: self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+            print(f"finishing processing {dial_idx-1} dialogs for {mode} set ...")
+        self.save_original_examples(data[:5], data_name)
+        self.save_converted_examples(data_name)
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+
+    def convai2(self):
+        """
+        incomplete dialog included, we remove dialog with equal or less than one turn"""
+        from datasets import load_dataset
+        data_name = "ConvAI2"
+        mode = "train"
+        data = load_dataset("conv_ai_2", split=mode)
+        data_df = data.to_pandas()
+        new_data, file_idx, dial_idx = {}, 1, 1
+        for i in (range(len(data_df))):
+            new_dial = self.init_dial(dial_idx=dial_idx)
+            new_dial_id = f"{data_name}--{mode}--{dial_idx}"
+            new_dial[ORI_DIAL_ID] = data_df["dialog_id"][i]
+            new_dial[ORI_DIAL_INFO]["id"] = data_df["id"][i]
+            new_dial[ORI_DIAL_INFO]["bot_profile"] = ["".join(persona) for persona in data_df["bot_profile"][i]]
+            new_dial[ORI_DIAL_INFO]["user_profile"] = ["".join(persona) for persona in data_df["user_profile"][i]]
+            new_dial[ORI_DIAL_INFO]["eval_score"] = int(data_df["eval_score"][i])
+            new_dial[ORI_DIAL_INFO]["profile_match"] = int(data_df["profile_match"][i])
+            if len(data_df["dialog"][i]) <= 2: continue
+            if "Text is not given." in " ".join([turn["text"] for turn in data_df["dialog"][i]]): continue
+            dial_hist = []
+            for turn_idx, turn in enumerate(data_df["dialog"][i]):
+                if turn_idx % 2 == 0:
+                    new_turn = self.init_turn(turn_id=turn_idx//2+1)
+                    new_turn[DIAL_HIST] = " ".join(dial_hist)
+                    new_turn[USR_UTT] = turn["text"]
+                    new_turn[ORI_USR_ANN]["id"] = turn["id"]
+                    new_turn[ORI_USR_ANN]["sender"] = turn["sender"]
+                    new_turn[ORI_USR_ANN]["sender_class"] = turn["sender_class"]
+
+                    dial_hist.append(f"<{SPEAKER1.upper()}> " + new_turn[USR_UTT])
+                else:
+                    new_turn[SYS_UTT] = turn["text"]
+                    new_turn[ORI_SYS_ANN]["id"] = turn["id"]
+                    new_turn[ORI_SYS_ANN]["sender"] = turn["sender"]
+                    new_turn[ORI_SYS_ANN]["sender_class"] = turn["sender_class"]
+                    dial_hist.append(f"<{SPEAKER2.upper()}> " + new_turn[SYS_UTT])
+                    new_dial[LOG].append(new_turn)
+            if not new_turn[SYS_UTT]:
+                new_dial[LOG].append(new_turn)
+            new_data[new_dial_id] = new_dial
+            if new_dial[DIAL_IDX] % 10000 == 0:
+                self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+                new_data = {} # reset
+                file_idx += 1
+            dial_idx += 1
+        print(f"finishing processing {dial_idx-1} dialogs for {mode} set ...")
+        if new_data: self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+        self.save_original_examples(data[:5], data_name)
+        self.save_converted_examples(data_name)
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+
+    def antiscam(self):
+        """
+        0: attacker
+        1: agent
+        0 always starts conversation 
+        1 always ends conversation
+        """
+        data_name = "AntiScam"
+        data = self._load_txt(os.path.join(self.data_dir, data_name, "data/AntiScam_all.txt"), encoding='latin-1')
+        new_data, file_idx, dial_idx, turn_idx, dial_hist = {}, 1, 1, 1, []
+        mode = "train"
+        new_dial = self.init_dial(dial_idx=dial_idx)
+        new_turn = self.init_turn(turn_id=turn_idx)
+        for row in (data):
+            speaker, utt = row.split("\t")
+            if speaker == "0":
+                if new_turn[SYS_UTT]: # start a new turn
+                    # wrap up the previous turn
+                    new_dial[LOG].append(new_turn)
+                    turn_idx += 1
+                    dial_hist.append(f"<{SPEAKER1.upper()}> " + new_turn[USR_UTT])
+                    dial_hist.append(f"<{SPEAKER2.upper()}> " + new_turn[SYS_UTT])
+                    # start a new turn
+                    new_turn = self.init_turn(turn_id=turn_idx)
+                    new_turn[DIAL_HIST] = " ".join(dial_hist)
+                    new_turn[USR_UTT] = utt.strip('\"')
+                else: # multiple utt from '0'
+                    new_turn[USR_UTT] += " " + utt.strip('\"')
+                    new_turn[USR_UTT] = new_turn[USR_UTT].strip()
+            elif speaker == "1":
+                new_turn[SYS_UTT] += " " + utt.strip('"')
+                new_turn[SYS_UTT] = new_turn[SYS_UTT].strip()
+            elif not speaker: # finish a dialog
+                if new_turn[SYS_UTT]: # wrap up the previous turn
+                    new_dial[LOG].append(new_turn)
+                new_dial_id = f"{data_name}--{mode}--{dial_idx}"
+                new_data[new_dial_id] = new_dial
+                if dial_idx % 10000 == 0:
+                    self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+                    new_data = {} # reset
+                    file_idx += 1
+                dial_idx += 1
+                turn_idx = 1
+                dial_hist = []
+                new_dial = self.init_dial(dial_idx=dial_idx)
+                new_turn = self.init_turn(turn_id=turn_idx)
+            else:
+                raise ValueError("Unknown speaker ... ")
+        if new_turn[SYS_UTT]:
+            new_dial[LOG].append(new_turn)
+        new_dial_id = f"{data_name}--{mode}--{dial_idx}"
+        new_data[new_dial_id] = new_dial
+        print(f"finishing processing {dial_idx} dialogs for {mode} set ...")
+        self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+
+        if new_data: self.save_dial(new_data, data_name=data_name, file_idx=file_idx, mode=mode)
+        self.save_original_examples(data[:150], data_name)
+        self.save_converted_examples(data_name)
+        print("*"*10, f"finishing processing dataset {data_name}", "*"*10)
+
+
+
+
+    def run_all(self):
+        # self.places()
+        # self.chitchat()
+        # self.prosocial()
+        # self.hhrlhf()
+        # self.empathetic()
+        # self.convai2()
+        self.antiscam()
+
+
+    def copy_example(self):
+        source_dir = self.save_dir
+        for target_dir in [ "/home/qkun/projs/TOD-Project/Datasets/Open-Domain_PROCESSED/", "/home/qkun/projs/DialogStudio-Release/open-domain-dialogues/"]:
+            # target_dir = "/home/qkun/projs/TOD-Project/Datasets/Open-Domain_PROCESSED/"
+            # target_dir2 = "/home/qkun/projs/DialogStudio-Release/open-domain-dialogues/"
+            file_list = ["converted_examples.json", "original_examples.json", "readme.txt", "LICENSE"]
+            for dir_name in sorted(os.listdir(source_dir)):
+                if os.path.isfile(os.path.join(source_dir, dir_name)): continue
+                if not os.path.exists(os.path.join(target_dir, dir_name)): os.makedirs(os.path.join(target_dir, dir_name))
+                for filename in file_list:
+                    source_path = os.path.join(source_dir, dir_name, filename)
+                    target_path = os.path.join(target_dir, dir_name, filename)
+                    if not os.path.exists(source_path): continue
+                    shutil.copy(source_path, target_path)
+
+
+def main():
+    preprocess = PreProcessData()
+    preprocess.run_all()
+    preprocess.copy_example()
+
+if __name__ == '__main__':
+    main()

code/utils/constant.py

@@ -0,0 +1,55 @@
+"""
+ Copyright (c) 2023, salesforce.com, inc.
+ All rights reserved.
+ SPDX-License-Identifier: Apache License 2.0
+ For full license text, see the LICENSE file in the repo root or https://www.apache.org/licenses/LICENSE-2.0
+"""
+
+#!/usr/bin/env python3
+#
+
+# key used for direct usage
+SPEAKER1 = "user"
+SPEAKER2 = "system"
+ORI_DIAL_ID = "original dialog id"
+DIAL_IDX = "dialog index"
+ORI_DIAL_INFO = "original dialog info"
+TURN_ID = "turn id"
+USR_UTT = f"{SPEAKER1} utterance"
+SYS_UTT = f"{SPEAKER2} response"
+DIAL_HIST = "dialog history"
+ORI_USR_ANN = f"original {SPEAKER1} side information"
+ORI_SYS_ANN = f"original {SPEAKER2} side information"
+LOG = "log"
+
+# # # output for different task
+# domain prediction
+DOM = "domain"
+# intent prediction, including dialog act prediction if intent missing
+INTENT = "intent"
+INTENT_SPLIT = " , "
+# dst
+DST = "dst"
+DST_ACC = "dst accumulated"
+DST_SPLIT = " , "
+
+# # # used for external knowledge
+EK = "external knowledge"
+EK_DST = "dst knowledge"
+EK_INTENT = "intent knowledge"
+# non-flat external knowledge dictionary
+EK_ORI = "external knowledge non-flat"
+TOD_EK = "metadata"
+TOD_LENGTH = 10
+# DOM_EK = "domains"
+INTENT_EK = "intents"
+DST_EK = "slots and values"
+DST_LENGTH = 10
+
+# # # prompt for each dialog
+PROMPT = "prompt"
+PROMPT_DST = "prompt for dst task"
+PROMPT_INTENT = "prompt for intent prediction"
+
+MULTIWOZ_DOMAINS = ["taxi", "police", "hospital", "hotel","attraction","train","restaurant"]
+

code/utils/constant_tod.py

@@ -0,0 +1,56 @@
+"""
+ Copyright (c) 2023, salesforce.com, inc.
+ All rights reserved.
+ SPDX-License-Identifier: Apache License 2.0
+ For full license text, see the LICENSE file in the repo root or https://www.apache.org/licenses/LICENSE-2.0
+"""
+
+
+#!/usr/bin/env python3
+#
+
+# key used for direct usage
+SPEAKER1 = "user"
+SPEAKER2 = "system"
+ORI_DIAL_ID = "original dialog id"
+DIAL_IDX = "dialog index"
+ORI_DIAL_INFO = "original dialog info"
+TURN_ID = "turn id"
+USR_UTT = f"{SPEAKER1} utterance"
+SYS_UTT = f"{SPEAKER2} response"
+DIAL_HIST = "dialog history"
+ORI_USR_ANN = f"original {SPEAKER1} side information"
+ORI_SYS_ANN = f"original {SPEAKER2} side information"
+LOG = "log"
+
+# # # output for different task
+# domain prediction
+DOM = "domain"
+# intent prediction, including dialog act prediction if intent missing
+INTENT = "intent"
+INTENT_SPLIT = " , "
+# dst
+DST = "dst"
+DST_ACC = "dst accumulated"
+DST_SPLIT = " , "
+
+# # # used for external knowledge
+EK = "external knowledge"
+EK_DST = "dst knowledge"
+EK_INTENT = "intent knowledge"
+# non-flat external knowledge dictionary
+EK_ORI = "external knowledge non-flat"
+TOD_EK = "metadata"
+TOD_LENGTH = 10
+# DOM_EK = "domains"
+INTENT_EK = "intents"
+DST_EK = "slots and values"
+DST_LENGTH = 10
+
+# # # prompt for each dialog
+PROMPT = "prompt"
+PROMPT_DST = "prompt for dst task"
+PROMPT_INTENT = "prompt for intent prediction"
+
+MULTIWOZ_DOMAINS = ["taxi", "police", "hospital", "hotel","attraction","train","restaurant"]
+

code/utils/domain_mapping.py

@@ -0,0 +1,238 @@
+"""
+ Copyright (c) 2023, salesforce.com, inc.
+ All rights reserved.
+ SPDX-License-Identifier: Apache License 2.0
+ For full license text, see the LICENSE file in the repo root or https://www.apache.org/licenses/LICENSE-2.0
+"""
+
+
+#!/usr/bin/env python3
+import sys, os
+import random
+
+templates = [
+    "This is a bot helping users to _____. Given the dialog context and external database, please generate a relevant system response for the user.",
+    "This bot assists users to _____. Based on the dialogue context and information from the external database, please generate an appropriate response for the user.",
+    "This bot helps users to _____. Provide a suitable response to the user, keeping in mind the conversation history and accessible external data.",
+    "The purpose of this bot is to assist users to _____. Considering the dialogue context and the information available in the external knowledge, please provide a fitting response for the user.",
+    "This bot is designed to help users _____. By utilizing the current dialog context and external resources, generate an appropriate response for the user."
+]
+
+mapping = {
+    "ABCD":{
+        "product_defect": "solve issues about refunds and returns",
+        "storewide_query": "find answers to FAQ questions about pricing, timing, membership or features",
+        "shipping_issue": "check out update a shipment of an item",
+        "subscription_inquiry": "updates premium subscription",
+        "account_access": "manage account access information",
+        "troubleshoot_site": "solve website-related issues", # website slow, search not working, credit card, cart not updating
+        "single_item_query": "find answers to FAQ questions about clothes",
+        "order_issue": "get status of an order or change an order",
+        "purchase_dispute": "dispute a purchase",
+        "manage_account": "manage account profile",
+    },
+    "AirDialogue":{
+        "flight": "book a flight ticket",
+    },
+    "BiTOD":{
+        "restaurants": "find and book a restaurant",
+        "attractions": "find a tourist attraction",
+        "HKMTR": "find a metro line",
+        "weathers": "search weather information",
+        "hotels": "find and book a hotel",
+    },
+    "CaSiNo":{
+        "negotiate": "take the role of campsite neighbors and negotiate for food, water, and firewood" # not help to finish task
+    },
+    "CraigslistBargains":{
+        "bargain": "bargain for goods" # can be devided into different items e.g. housing, bike, electronics
+    },
+    "DSTC2-Clean":{
+        "restaurant": "find a restaurant"
+    },
+    "FRAMES":{
+        "trip": "book a trip"
+    },
+    "KVRET":{
+        "schedule":"manage a calendar",
+        "weather":"find weather information",
+        "navigate":"get navigation",
+    },
+    "WOZ2_0":{
+        "restaurant":"find a restaurant",
+    },
+    "SGD":{
+        "alarm": "manage alarms",
+        "banks": "manage bank accounts",
+        "buses": "book a bus journey",
+        "events": "book an event ticket",
+        "flights": "book a flight ticket",
+        "homes": "find an apartment or schedule an apartment viewing", # Homes_2 : Service for finding properties to buy and rent"
+        "hotels": "book a hotel",
+        "media": "rent a movie to watch",
+        "music": "find a song",
+        "rentalcars": "rent a car",
+        "restaurants": "book a restaurant",
+        "ridesharing": "book a ride",
+        "services": "reserve a therapist, dentists, doctor or hair stylist", # Services_1: hair stylist; _2:dentists; Services_4: therapist
+        "travel": "find a tourist attraction",
+        "weather": "get weather information",
+        "messaging": "connect and share locations", # Messaging_1:Connect and share locations with your contact
+        "movies": "book a movie ticket",
+        "payment": "manage a payment", # payment_1 The fast, simple way to pay in apps, on the web, and in millions of stores
+        "trains": "book a train journey",
+        "calendar": "manage a calendar",
+    },
+    "MetaLWOZ":{
+        "update_calendar": "schedule meetings on a calendar",
+        "order_pizza": "order a pizza",
+        "movie_listings": "get movie information",
+        "event_reserve": "make reservations for events",
+        "weather_check": "get weather information",
+        "update_contact": "update cell phone contacts",
+        "make_restaurant_reservations": "reserve a restaurant",
+        "edit_playlist": "manage music playlists",
+        "look_up_info": "fetch information from the internet",
+        "shopping": "order products from website",
+        "store_details": "get information about stores and businesses",
+        "sports_info": "get sports information",
+        "quote_of_the_day_bot": "get a quote of the day",
+        "how_to_basic": "get instructions for basic tasks",
+        "prompt_generator": "get creative prompts",
+        "library_request": "get library information",
+        "bank_bot": "manage bank accounts",
+        "restaurant_picker": "find a restaurant",
+        "phone_plan_bot": "get mobile phone service",
+        "name_suggester": "get names for things",
+        "city_info": "get facts about different cities",
+        "music_suggester": "get music suggestions",
+        "agreement_bot": "get agreements",
+        "pet_advice": "get pet advice",
+        "apartment_finder": "find an apartment",
+        "guiness_check": "get world records",
+        "geography": "get to know where countries are",
+        "alarm_set": "manage alarms",
+        "contact_manager": "manage the user's contacts",
+        "phone_settings": "manage the user's phone's settings",
+        "appointment_reminder": "confirm their appointments",
+        "home_bot": "manage the user's home",
+        "policy_bot": "get information about a company's policies",
+        "decider_bot": "make decisions for the user",
+        "catalogue_bot": "search a catalogue",
+        "ski_bot": "book skiing trips",
+        "bus_schedule_bot": "manage public transit schedules",
+        "insurance": "get insurance information",
+        "what_is_it": "remember what a thing is.",
+        "auto_sort": "sort things",
+        "scam_lookup": "get about various scams",
+        "time_zone": "get information about time zones",
+        "play_times": "schedule shows during a theatre festival",
+        "game_rules": "know the rules for games",
+        "wedding_planner": "plan weddings",
+        "check_status": "check the status of things",
+        "present_ideas": "get advice on gift giving",
+        "booking_flight": "book a flight ticket",
+        "hotel_reserve": "book rooms in a hotel",
+        "vacation_ideas": "plan for vacations and trips",
+        "tourism": "get tourism related advices"
+},
+    "STAR":{
+        "apartment": "find an apartment or schedule an apartment viewing",
+        "bank": "manage bank accounts", # Check the balance / Report suspicious behavior 
+        "doctor": "make an appointment with a doctor", # appointment Make an appointment with a doctor / followup doctor appointment Check instructions given by doctor upon last visit
+        "hotel": "book a hotel", # find / book a hotel or call for room service
+        "meeting": "schedule a meeting",
+        "party": "plan a party", # plan Plan a party at a given venue, party rsvp RSVP to a party of a given host at a given venue
+        "plane": "book a flight ticket", # search Find a flight between two cities / plane reserve Book a flight, given its id
+        "restaurant": "reserve a restaurant", # search Find a restaurant / restaurant reserve Reserve a table at a restaurant
+        "ride": "book a ride", #  book ride Call a Taxi/Uber/Lyft ride to any destination / ride change Change details of a Taxi/Uber/Lyft ride that had been called earlier / ride status Check the status of a ride you called earlier
+        "spaceship": "solve issues with a spaceship", # life support Recover the spaceship’s life support / spaceship access codes Get a repair robot to open a door for you
+        "trip": "get navigation", # directions Get walking/driving/transit directions between two locations (B).
+        "trivia": "plan a game of trivia", # Play a game of trivia (C).
+        "weather": "get weather information", # Check the weather (forecast) in various cities
+    },
+    "Taskmaster1":{
+        "restaurant": "reserve a restaurant",
+        "movie": "book a movie ticket",
+        "pizza": "order a pizza",
+        "coffee": "order coffee drinks",
+        "auto": "make appointment for auto repair",
+        "uber": "book a uber ride",
+    },
+    "Taskmaster2":{ # domains can be split further into subdomains based on instruction_id e.g. sports --> nba, nfl, epl
+        "flights": "book a flight ticket",
+        "food-ordering": "make a take-out order",
+        "hotels":"find a hotel",
+        "movies":"find a movie to watch",
+        "music": "find music tracks",
+        "restaurant-search": "find a restaurant",
+        "sports": "get sports information",
+    },
+    "Taskmaster3":{
+        "movie": "book a movie ticket",
+    },
+    "SimJointMovie":{
+        "movie": "book a movie ticket",
+    },
+    "SimJointRestaurant":{
+        "restaurant": "reserve a restaurant",
+    },
+    "SimJointGEN":{
+        "movie": "book a movie ticket",
+    },
+    "MulDoGO":{
+        "airline": "book a flight ticket", # e domain dialogues focus on booking airline flights, selecting or changing seat assignments, and requesting boarding passes;
+        "fastfood": "order fast food", # domain is the least similar to the others, as the intents primarily involve ordering food and the slots quantify their order.
+        "finance": "manage bank accounts", # domain simulates dialogues a customer may have with a bank. These include opening a bank account, checking their balance, and reporting a lost credit card;
+        "insurance": "get insurance information", # domain simulates users calling about their insurance policy or requesting the fulfillment of a policy on their car or phone
+        "media": "order a media service", # domain simulates dialogues a customer may have ordering a service or paying bills related to telecommunications. 
+        "software": "get software service information", # domain involves customers inquiring about software services: products, outages, promotions, and bills
+    },
+    "MS-DC":{
+        "restaurant": "reserve a restaurant",
+        "taxi": "book a taxi",
+        "movie": "book a movie ticket",
+    },
+    "SalesBot":{
+        "GetTimesForMovie": "get information for a movie",
+        "LookupSong": "find a song",
+        "FindMovies": "find a movie to watch",
+        "LookupMusic": "find and play a song",
+        "PlaySong": "play a song",
+        "FindAttractions": "find a tourist attraction",
+    },
+    "MuDoCo":{
+        "calling": "make a call", # user initiates or manipulates a voice or video call
+        "messaging": "send or read messages", # user sends or reads messages, asks for information about their message queue
+        "music": "find a song", # user searches for music by a certain artist or in a certain genre, asks the system to play songs, etc.
+        "news": "get news information", # user asks for information about current events related to a variety of topics
+        "reminders": "modify a reminder", # user sets, modifies, queries or deletes reminders for a certain date or time
+        "weather": "get weather information", # user asks about the current or future weather conditions in various locations
+    },
+    "MULTIWOZ2_2":{
+        "restaurant": "find a restaurant",
+        "hotel": "find a hotel",
+        "attraction": "find an attraction",
+        "train": "book a train ticket",
+        "taxi": "find a taxi",
+        "hospital": "find a hospital",
+        "police": "find a police station",
+        "bus": "find a bus",
+    },
+}
+
+def generate_prompt(data_name, domains, num_sample=1):
+    """
+    Including all 5 types of prompt and output a list
+    """
+    # sampled_template = random.choice(templates)
+    descriptions = [mapping[data_name][domain] for domain in domains]
+    if len(descriptions) == 1:
+        description_str = descriptions[0]
+    elif len(descriptions) == 2:
+        description_str = " and ".join(descriptions)
+    elif len(descriptions) == 0:
+        description_str = "complete specified tasks"
+    else:
+        description_str = "complete multiple tasks, e.g. " + ", ".join(descriptions[:-1]) + ", and " + descriptions[-1]
+    return [sampled_template.replace("_____", description_str) for sampled_template in templates]

conversational-recommendation-dialogues/DuRecDial-2.0/LICENSE.txt

@@ -0,0 +1,201 @@
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conversational-recommendation-dialogues/DuRecDial-2.0/README.md

@@ -0,0 +1,75 @@
+# DuRecDial
+
+In this paper, we provide a **bilingual parallel** human-to-human recommendation dialog dataset, **DuRecDial 2.0**, to enable researchers to explore the challenging task of multilingual and cross-lingual conversational recommendation. The difference between DuRecDial 2.0 and existing conversational recommendation datasets is that the data item (Profile, Goal, Knowledge, Context, Response) in DuRecDial 2.0 is annotated in two languages, both English and Chinese, while other datasets are built with the setting of a single language. We collect **8.2k** dialogues aligned across English and Chinese languages (16.5k dialogs and 255k utterances in total) that are annotated by crowdsourced workers with strict quality control procedure. DuRecDial 2.0 provides a challenging testbed for future studies of monolingual, multilingual, and cross-lingual conversational recommendation. For a detailed introduction of DuRecDial 2.0, please refer to [DuRecDial](https://github.com/liuzeming01/Research/tree/master/NLP/ACL2020-DuRecDial) on [IEEE Xplore](https://ieeexplore.ieee.org/document/9699426), [ACL Anthology](https://aclanthology.org/2020.acl-main.98/) and [arXiv](https://arxiv.org/abs/2005.03954).
+
+Our paper on [ACL Anthology](https://aclanthology.org/2021.emnlp-main.356/) and [arXiv](https://arxiv.org/abs/2109.08877) . If the corpus is helpful to your research, please kindly cite our paper:
+
+```bib
+@inproceedings{liu-etal-2021-durecdial,
+    title = "{D}u{R}ec{D}ial 2.0: A Bilingual Parallel Corpus for Conversational Recommendation",
+    author = "Liu, Zeming  and
+      Wang, Haifeng  and
+      Niu, Zheng-Yu  and
+      Wu, Hua  and
+      Che, Wanxiang",
+    booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
+    month = nov,
+    year = "2021",
+    address = "Online and Punta Cana, Dominican Republic",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2021.emnlp-main.356",
+    doi = "10.18653/v1/2021.emnlp-main.356",
+    pages = "4335--4347",
+}
+```
+
+## Data
+
+**Note:If the first goal is "Greetings/寒暄", the seeker starts the conversation, otherwise, the user starts the conversation.**
+
+An example of the conversation in DuRecDial 2.0:
+
+![example](figs/example8-1.png)
+
+DuRecDial 2.0 is an extension of the [DuRecDial](https://baidu-nlp.bj.bcebos.com/DuRecDial.zip). Specifically, we extend the DuRecDial to English by crowdsourced workers with strict quality control procedure.
+
+If DuRecDial is helpful to your research, please kindly cite our papers:
+
+```bib
+@inproceedings{liu-etal-2020-towards-conversational,
+    title = "Towards Conversational Recommendation over Multi-Type Dialogs",
+    author = "Liu, Zeming  and
+      Wang, Haifeng  and
+      Niu, Zheng-Yu  and
+      Wu, Hua  and
+      Che, Wanxiang  and
+      Liu, Ting",
+    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
+    month = jul,
+    year = "2020",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2020.acl-main.98",
+    doi = "10.18653/v1/2020.acl-main.98",
+    pages = "1036--1049",
+}
+```
+```bib
+@ARTICLE{9699426,
+  author={Liu, Zeming and Zhou, Ding and Liu, Hao and Wang, Haifeng and Niu, Zheng-Yu and Wu, Hua and Che, Wanxiang and Liu, Ting and Xiong, Hui},
+  journal={IEEE Transactions on Knowledge and Data Engineering}, 
+  title={Graph-Grounded Goal Planning for Conversational Recommendation}, 
+  year={2023},
+  volume={35},
+  number={5},
+  pages={4923-4939},
+  doi={10.1109/TKDE.2022.3147210}
+  }
+```
+
+
+## License
+
+Apache License 2.0 and CC BY-NC-SA 4.0.
+
+Since DuRecDial 2.0 is licensed under CC BY-NC-SA 4.0. Note the dataset may not be adopted for commercial use.

conversational-recommendation-dialogues/DuRecDial-2.0/converted_examples.json

@@ -0,0 +1,998 @@
+{
+    "DuRecDial-2.0--train--1": {
+        "original dialog id": "",
+        "dialog index": 1,
+        "original dialog info": {
+            "goal": "[1] Q&A(Cecilia Cheung)-->[2] Chat about stars(Cecilia Cheung)-->[3] Movie recommendation(Failan)-->[4] Movie recommendation(The Stool Pigeon)-->[5]Say goodbye",
+            "user_profile": {
+                "Age Range": "Under 18 years old",
+                "Name": "Fangyang Liu",
+                "Residence": "Qingdao",
+                "Accepted food": "Jiaozi\u00a0Stuffed\u00a0with\u00a0Mackerel\u00a0",
+                "Accepted movies": [
+                    "Left Right Love Destiny",
+                    "Hot Summer Days",
+                    "Fly Me to Polaris",
+                    "Help!!!",
+                    "One Night in Mongkok",
+                    "The Bullet Vanishes"
+                ],
+                "Accepted Music": [
+                    "Once"
+                ],
+                "Rejected music": [
+                    "It's Time"
+                ],
+                "Gender": "Female",
+                "Accepted celebrities": [
+                    "Cecilia Cheung",
+                    "Kris Wu",
+                    "Nicholas Tse"
+                ],
+                "Accepted movie": [
+                    "The Legend of Speed"
+                ],
+                "Reject": [
+                    "News"
+                ],
+                "Rejected movies": [
+                    "Everyday is Valentine",
+                    "Unforgettable",
+                    "King of Comedy"
+                ],
+                "Occupation": "Student",
+                "Accepted music": "Time Boils The Rain",
+                "Accepted POI": [
+                    "Minguo Seafood Dumpling House"
+                ]
+            },
+            "conversation": [
+                "[1] Who is the leading actor of the movie Left Right Love Destiny?",
+                "It's Cecilia Cheung",
+                "You even know that. Excellent!",
+                "[2] Thank you for your praise. She's a Chinese idol. Of course I know her.",
+                "Yes my idol is quite unusual.",
+                "She is also an Asian Outstanding Artist in New York Chinese Film Festival. Excellent.",
+                "Yes. People like her will shine wherever they go.",
+                "[3] Then don't miss her movie Failan. It shows a love tragedy in which the two people are secluded in different time spaces. However, the movie doesn't just tell a sad but beautiful love story. Through the story, the audiences can see the director's profound thinking and understanding of life and human nature.",
+                "Although I really like her, I prefer to see Nicholas Tse's movies.",
+                "[4] Then you can watch Nicholas Tse's movie The Stool Pigeon. His acting is good.",
+                "What kind of movie is it?",
+                "It's an action drama, with a little bit of thriller.",
+                "Woah, sounds interesting.",
+                "I'm sure you'll like it.",
+                "[5] Then I'm leaving too see the movie.",
+                "Okay, see you next time."
+            ],
+            "goal_topic_list": [
+                "Left Right Love Destiny",
+                "Left Right Love Destiny",
+                "Left Right Love Destiny",
+                "Cecilia Cheung",
+                "Cecilia Cheung",
+                "Cecilia Cheung",
+                "Cecilia Cheung",
+                "Failan",
+                "Failan",
+                "The Stool Pigeon",
+                "The Stool Pigeon",
+                "The Stool Pigeon",
+                "The Stool Pigeon",
+                "The Stool Pigeon",
+                "Say goodbye",
+                "Say goodbye"
+            ],
+            "goal_type_list": [
+                "Q&A",
+                "Q&A",
+                "Q&A",
+                "Chat about stars",
+                "Chat about stars",
+                "Chat about stars",
+                "Chat about stars",
+                "Movie recommendation",
+                "Movie recommendation",
+                "Movie recommendation",
+                "Movie recommendation",
+                "Movie recommendation",
+                "Movie recommendation",
+                "Movie recommendation",
+                "Say goodbye",
+                "Say goodbye"
+            ],
+            "situation": "Time: 12:00, at school",
+            "knowledge": [
+                [
+                    "Cecilia Cheung",
+                    "Stars",
+                    "Left Right Love Destiny"
+                ],
+                [
+                    "Cecilia Cheung",
+                    "Stars",
+                    "Left Right Love Destiny"
+                ],
+                [],
+                [
+                    "Cecilia Cheung",
+                    "Intro",
+                    "Chinese dreamgirl"
+                ],
+                [],
+                [
+                    "Cecilia Cheung",
+                    "Achievement",
+                    "Outstanding Asian artists of New York China Film Festival"
+                ],
+                [],
+                [
+                    "Failan",
+                    "Comments",
+                    "Failan presents a love tragedy isolated in different time and space, but the film does not stop at telling a sad and beautiful love. Through the shell of the sad story, the audience gets the director's deeper thinking and understanding of the human nature of life.Focusing on the spiritual core of saving and being saved, the narrative unfolds, the theme is expounded, and the blindness to reality is unveiled. The audience is touched and awakened. The director fully played the magic of the movie, disrupting the narrative time and space, intersecting the past and the present, and advancing freely following the protagonists\u2019 emotions, making the story structure more tense and the theme and emotions more heartfelt. Although it describes the underworld, the director deliberately avoided the violence rendering and used extremely life-like methods to describe the underworld story routines such as gang struggle and group fight."
+                ],
+                [],
+                [
+                    "Nicholas Tse",
+                    "Stars",
+                    "The Stool Pigeon"
+                ],
+                [
+                    "The Stool Pigeon",
+                    "Type",
+                    "Action plot Thriller"
+                ],
+                [
+                    "The Stool Pigeon",
+                    "Type",
+                    "Action plot Thriller"
+                ],
+                [],
+                [],
+                [],
+                []
+            ]
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Who is the leading actor of the movie Left Right Love Destiny?",
+                "system response": "It's Cecilia Cheung",
+                "dialog history": "",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 2,
+                "user utterance": "You even know that. Excellent!",
+                "system response": "Thank you for your praise. She's a Chinese idol. Of course I know her.",
+                "dialog history": "<USER> Who is the leading actor of the movie Left Right Love Destiny? <SYSTEM> It's Cecilia Cheung",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 3,
+                "user utterance": "Yes my idol is quite unusual.",
+                "system response": "She is also an Asian Outstanding Artist in New York Chinese Film Festival. Excellent.",
+                "dialog history": "<USER> Who is the leading actor of the movie Left Right Love Destiny? <SYSTEM> It's Cecilia Cheung <USER> You even know that. Excellent! <SYSTEM> Thank you for your praise. She's a Chinese idol. Of course I know her.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 4,
+                "user utterance": "Yes. People like her will shine wherever they go.",
+                "system response": "Then don't miss her movie Failan. It shows a love tragedy in which the two people are secluded in different time spaces. However, the movie doesn't just tell a sad but beautiful love story. Through the story, the audiences can see the director's profound thinking and understanding of life and human nature.",
+                "dialog history": "<USER> Who is the leading actor of the movie Left Right Love Destiny? <SYSTEM> It's Cecilia Cheung <USER> You even know that. Excellent! <SYSTEM> Thank you for your praise. She's a Chinese idol. Of course I know her. <USER> Yes my idol is quite unusual. <SYSTEM> She is also an Asian Outstanding Artist in New York Chinese Film Festival. Excellent.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 5,
+                "user utterance": "Although I really like her, I prefer to see Nicholas Tse's movies.",
+                "system response": "Then you can watch Nicholas Tse's movie The Stool Pigeon. His acting is good.",
+                "dialog history": "<USER> Who is the leading actor of the movie Left Right Love Destiny? <SYSTEM> It's Cecilia Cheung <USER> You even know that. Excellent! <SYSTEM> Thank you for your praise. She's a Chinese idol. Of course I know her. <USER> Yes my idol is quite unusual. <SYSTEM> She is also an Asian Outstanding Artist in New York Chinese Film Festival. Excellent. <USER> Yes. People like her will shine wherever they go. <SYSTEM> Then don't miss her movie Failan. It shows a love tragedy in which the two people are secluded in different time spaces. However, the movie doesn't just tell a sad but beautiful love story. Through the story, the audiences can see the director's profound thinking and understanding of life and human nature.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 6,
+                "user utterance": "What kind of movie is it?",
+                "system response": "It's an action drama, with a little bit of thriller.",
+                "dialog history": "<USER> Who is the leading actor of the movie Left Right Love Destiny? <SYSTEM> It's Cecilia Cheung <USER> You even know that. Excellent! <SYSTEM> Thank you for your praise. She's a Chinese idol. Of course I know her. <USER> Yes my idol is quite unusual. <SYSTEM> She is also an Asian Outstanding Artist in New York Chinese Film Festival. Excellent. <USER> Yes. People like her will shine wherever they go. <SYSTEM> Then don't miss her movie Failan. It shows a love tragedy in which the two people are secluded in different time spaces. However, the movie doesn't just tell a sad but beautiful love story. Through the story, the audiences can see the director's profound thinking and understanding of life and human nature. <USER> Although I really like her, I prefer to see Nicholas Tse's movies. <SYSTEM> Then you can watch Nicholas Tse's movie The Stool Pigeon. His acting is good.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 7,
+                "user utterance": "Woah, sounds interesting.",
+                "system response": "I'm sure you'll like it.",
+                "dialog history": "<USER> Who is the leading actor of the movie Left Right Love Destiny? <SYSTEM> It's Cecilia Cheung <USER> You even know that. Excellent! <SYSTEM> Thank you for your praise. She's a Chinese idol. Of course I know her. <USER> Yes my idol is quite unusual. <SYSTEM> She is also an Asian Outstanding Artist in New York Chinese Film Festival. Excellent. <USER> Yes. People like her will shine wherever they go. <SYSTEM> Then don't miss her movie Failan. It shows a love tragedy in which the two people are secluded in different time spaces. However, the movie doesn't just tell a sad but beautiful love story. Through the story, the audiences can see the director's profound thinking and understanding of life and human nature. <USER> Although I really like her, I prefer to see Nicholas Tse's movies. <SYSTEM> Then you can watch Nicholas Tse's movie The Stool Pigeon. His acting is good. <USER> What kind of movie is it? <SYSTEM> It's an action drama, with a little bit of thriller.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 8,
+                "user utterance": "Then I'm leaving too see the movie.",
+                "system response": "Okay, see you next time.",
+                "dialog history": "<USER> Who is the leading actor of the movie Left Right Love Destiny? <SYSTEM> It's Cecilia Cheung <USER> You even know that. Excellent! <SYSTEM> Thank you for your praise. She's a Chinese idol. Of course I know her. <USER> Yes my idol is quite unusual. <SYSTEM> She is also an Asian Outstanding Artist in New York Chinese Film Festival. Excellent. <USER> Yes. People like her will shine wherever they go. <SYSTEM> Then don't miss her movie Failan. It shows a love tragedy in which the two people are secluded in different time spaces. However, the movie doesn't just tell a sad but beautiful love story. Through the story, the audiences can see the director's profound thinking and understanding of life and human nature. <USER> Although I really like her, I prefer to see Nicholas Tse's movies. <SYSTEM> Then you can watch Nicholas Tse's movie The Stool Pigeon. His acting is good. <USER> What kind of movie is it? <SYSTEM> It's an action drama, with a little bit of thriller. <USER> Woah, sounds interesting. <SYSTEM> I'm sure you'll like it.",
+                "original user side information": {},
+                "original system side information": {}
+            }
+        ]
+    },
+    "DuRecDial-2.0--train--2": {
+        "original dialog id": "",
+        "dialog index": 2,
+        "original dialog info": {
+            "goal": "[1]Ask about weather-->[2] Food recommendation(Marinated Fish)-->[3] POI recommendation(Mr.Fish Roasted)-->[4]Say goodbye",
+            "user_profile": {
+                "Age Range": "Under 18 years old",
+                "Name": "Mingzheng Li",
+                "Residence": "Hengshui",
+                "Accepted food": "Marinated Fish",
+                "Accepted Music": [
+                    "You Will Always Be My Love",
+                    "After Leaving",
+                    "Lingering Memory of Past Love",
+                    "Still Think You're the Best",
+                    "I Waited Until the Flower Withered",
+                    "The Crescent",
+                    "Can't Fight The Feeling"
+                ],
+                "Rejected music": [
+                    "Coffee",
+                    "be torn with grief"
+                ],
+                "Gender": "Male",
+                "Favorite news": [
+                    "Jacky Cheung's news"
+                ],
+                "Accepted celebrities": [
+                    "Jacky Cheung"
+                ],
+                "Reject": [
+                    "Movie"
+                ],
+                "Accepted POI": "Mr.Fish Roasted",
+                "Accepted music": [
+                    "Wolf Legend"
+                ],
+                "Occupation": "Student"
+            },
+            "conversation": [
+                "[1] Baby, can you tell me the weather today?",
+                "OK, today in Hengshui it is sunny, with southwest winds. The high will be 4 \u2103 and low - 7 \u2103. Be sure to keep warm.",
+                "Wow, you're great. You know everything. Great!",
+                "[2] There's nothing I don't know. I also know that today's weather is suitable to eat Marinated Fish.",
+                "Okay, I like it.",
+                "I know a restaurant where the Marinated Fish is made of grouper.",
+                "Woah, there's grouper! I really like it! It's a tonic! I really want to have it!",
+                "[3] If you like it so much, I know a restaurant which cooks groupers very well. Mr.Fish Roasted. The Marinated Fish here is very authentic!",
+                "Then tell me about the average meal cost per person, the address and the ratings.",
+                "It costs 0 yuan per person. The address is the intersection of Liushi Road, Huzhuang commercial and residential building, Yingbin North Street, Jizhou District, Jizhou. 5 points, very high.",
+                "Okay. I'll be there tomorrow noon with my partner, taking her to have a taste. Hehe!",
+                "Okay, I'll make a reservation for you. I'll say bon appetite in advance!",
+                "[4] Thanks. Then I'm going to bed first. See you tomorrow. Bye.",
+                "All right. Bye~"
+            ],
+            "goal_topic_list": [
+                "Ask about weather",
+                "Ask about weather",
+                "Ask about weather",
+                "Marinated Fish",
+                "Marinated Fish",
+                "Marinated Fish",
+                "Marinated Fish",
+                "Mr.Fish Roasted",
+                "Mr.Fish Roasted",
+                "Mr.Fish Roasted",
+                "Mr.Fish Roasted",
+                "Mr.Fish Roasted",
+                "Say goodbye",
+                "Say goodbye"
+            ],
+            "goal_type_list": [
+                "Ask about weather",
+                "Ask about weather",
+                "Ask about weather",
+                "Food recommendation",
+                "Food recommendation",
+                "Food recommendation",
+                "Food recommendation",
+                "POI recommendation",
+                "POI recommendation",
+                "POI recommendation",
+                "POI recommendation",
+                "POI recommendation",
+                "Say goodbye",
+                "Say goodbye"
+            ],
+            "situation": "Time: 20 18 - 12 - 12   22:00, at home   Wednesday",
+            "knowledge": [
+                [
+                    "Hengshui",
+                    "2018-12-12",
+                    "Sunny with southwest winds. The high will be 4 \u2103, and low - 7 \u2103"
+                ],
+                [
+                    "Hengshui",
+                    "2018-12-12",
+                    "Sunny with southwest winds. The high will be 4 \u2103, and low - 7 \u2103"
+                ],
+                [],
+                [
+                    "Sunny with southwest winds. The high will be 4 \u2103, and low - 7 \u2103",
+                    "Perfect for having",
+                    "Marinated Fish"
+                ],
+                [],
+                [
+                    "Marinated Fish",
+                    "Ingredients",
+                    "grouper\u3001Olive oil\u3001lemon juice\u3001Garlic\u3001pepper powder\u3001salt"
+                ],
+                [],
+                [
+                    "Mr.Fish Roasted",
+                    "Specials",
+                    "Marinated Fish"
+                ],
+                [
+                    "Mr.Fish Roasted",
+                    "Rating",
+                    "5"
+                ],
+                [
+                    "Mr.Fish Roasted",
+                    "Rating",
+                    "5"
+                ],
+                [],
+                [],
+                [],
+                []
+            ]
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Baby, can you tell me the weather today?",
+                "system response": "OK, today in Hengshui it is sunny, with southwest winds. The high will be 4 \u2103 and low - 7 \u2103. Be sure to keep warm.",
+                "dialog history": "",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 2,
+                "user utterance": "Wow, you're great. You know everything. Great!",
+                "system response": "There's nothing I don't know. I also know that today's weather is suitable to eat Marinated Fish.",
+                "dialog history": "<USER> Baby, can you tell me the weather today? <SYSTEM> OK, today in Hengshui it is sunny, with southwest winds. The high will be 4 \u2103 and low - 7 \u2103. Be sure to keep warm.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 3,
+                "user utterance": "Okay, I like it.",
+                "system response": "I know a restaurant where the Marinated Fish is made of grouper.",
+                "dialog history": "<USER> Baby, can you tell me the weather today? <SYSTEM> OK, today in Hengshui it is sunny, with southwest winds. The high will be 4 \u2103 and low - 7 \u2103. Be sure to keep warm. <USER> Wow, you're great. You know everything. Great! <SYSTEM> There's nothing I don't know. I also know that today's weather is suitable to eat Marinated Fish.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 4,
+                "user utterance": "Woah, there's grouper! I really like it! It's a tonic! I really want to have it!",
+                "system response": "If you like it so much, I know a restaurant which cooks groupers very well. Mr.Fish Roasted. The Marinated Fish here is very authentic!",
+                "dialog history": "<USER> Baby, can you tell me the weather today? <SYSTEM> OK, today in Hengshui it is sunny, with southwest winds. The high will be 4 \u2103 and low - 7 \u2103. Be sure to keep warm. <USER> Wow, you're great. You know everything. Great! <SYSTEM> There's nothing I don't know. I also know that today's weather is suitable to eat Marinated Fish. <USER> Okay, I like it. <SYSTEM> I know a restaurant where the Marinated Fish is made of grouper.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 5,
+                "user utterance": "Then tell me about the average meal cost per person, the address and the ratings.",
+                "system response": "It costs 0 yuan per person. The address is the intersection of Liushi Road, Huzhuang commercial and residential building, Yingbin North Street, Jizhou District, Jizhou. 5 points, very high.",
+                "dialog history": "<USER> Baby, can you tell me the weather today? <SYSTEM> OK, today in Hengshui it is sunny, with southwest winds. The high will be 4 \u2103 and low - 7 \u2103. Be sure to keep warm. <USER> Wow, you're great. You know everything. Great! <SYSTEM> There's nothing I don't know. I also know that today's weather is suitable to eat Marinated Fish. <USER> Okay, I like it. <SYSTEM> I know a restaurant where the Marinated Fish is made of grouper. <USER> Woah, there's grouper! I really like it! It's a tonic! I really want to have it! <SYSTEM> If you like it so much, I know a restaurant which cooks groupers very well. Mr.Fish Roasted. The Marinated Fish here is very authentic!",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 6,
+                "user utterance": "Okay. I'll be there tomorrow noon with my partner, taking her to have a taste. Hehe!",
+                "system response": "Okay, I'll make a reservation for you. I'll say bon appetite in advance!",
+                "dialog history": "<USER> Baby, can you tell me the weather today? <SYSTEM> OK, today in Hengshui it is sunny, with southwest winds. The high will be 4 \u2103 and low - 7 \u2103. Be sure to keep warm. <USER> Wow, you're great. You know everything. Great! <SYSTEM> There's nothing I don't know. I also know that today's weather is suitable to eat Marinated Fish. <USER> Okay, I like it. <SYSTEM> I know a restaurant where the Marinated Fish is made of grouper. <USER> Woah, there's grouper! I really like it! It's a tonic! I really want to have it! <SYSTEM> If you like it so much, I know a restaurant which cooks groupers very well. Mr.Fish Roasted. The Marinated Fish here is very authentic! <USER> Then tell me about the average meal cost per person, the address and the ratings. <SYSTEM> It costs 0 yuan per person. The address is the intersection of Liushi Road, Huzhuang commercial and residential building, Yingbin North Street, Jizhou District, Jizhou. 5 points, very high.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 7,
+                "user utterance": "Thanks. Then I'm going to bed first. See you tomorrow. Bye.",
+                "system response": "All right. Bye~",
+                "dialog history": "<USER> Baby, can you tell me the weather today? <SYSTEM> OK, today in Hengshui it is sunny, with southwest winds. The high will be 4 \u2103 and low - 7 \u2103. Be sure to keep warm. <USER> Wow, you're great. You know everything. Great! <SYSTEM> There's nothing I don't know. I also know that today's weather is suitable to eat Marinated Fish. <USER> Okay, I like it. <SYSTEM> I know a restaurant where the Marinated Fish is made of grouper. <USER> Woah, there's grouper! I really like it! It's a tonic! I really want to have it! <SYSTEM> If you like it so much, I know a restaurant which cooks groupers very well. Mr.Fish Roasted. The Marinated Fish here is very authentic! <USER> Then tell me about the average meal cost per person, the address and the ratings. <SYSTEM> It costs 0 yuan per person. The address is the intersection of Liushi Road, Huzhuang commercial and residential building, Yingbin North Street, Jizhou District, Jizhou. 5 points, very high. <USER> Okay. I'll be there tomorrow noon with my partner, taking her to have a taste. Hehe! <SYSTEM> Okay, I'll make a reservation for you. I'll say bon appetite in advance!",
+                "original user side information": {},
+                "original system side information": {}
+            }
+        ]
+    },
+    "DuRecDial-2.0--train--3": {
+        "original dialog id": "",
+        "dialog index": 3,
+        "original dialog info": {
+            "goal": "[1] Music on demand(Hand in Hand)-->[2] Music recommendation(Change Me)-->[3] Play music(All the Things You Never Knew)-->[4]Say goodbye",
+            "user_profile": {
+                "Residence": "Yangzhou",
+                "Age Range": "Over 50 years old",
+                "Name": "Li Xu",
+                "Accepted food": "Marinated Fish",
+                "Favorite news": [
+                    "Bingbing Fan's news",
+                    "Leehom Wang's news"
+                ],
+                "Accepted movies": [
+                    "Tiles of Deception, Lurid Affections: The Making of 'Lust, Caution'"
+                ],
+                "Accepted Music": [
+                    "A Simple Song",
+                    "Heroes of Earth"
+                ],
+                "Rejected music": [
+                    "KISS GOODBYE"
+                ],
+                "Gender": "Male",
+                "Accepted celebrities": [
+                    "Bingbing Fan",
+                    "Leehom Wang"
+                ],
+                "Accepted movie": "Flash Point",
+                "Reject": [
+                    "Poi"
+                ],
+                "Rejected movies": [
+                    "Lust, Caution"
+                ],
+                "Accepted music": [
+                    "Hand in Hand"
+                ],
+                "Occupation": "Employed"
+            },
+            "conversation": [
+                "[1] Let's listen to Hand in Hand.",
+                "It's playing for you. Please enjoy it!",
+                "The songs of Leehom Wang are still so good.",
+                "[2] Then I recommend that you listen to Change Me, which is also sung by Leehom Wang. It's a song with a rock&roll style. Unlike Leehom Wang's previous works which are exciting and passionate, it starts from the bottom of the heart and finds the emotion in the ordinary with a calm heart.",
+                "I\u2018ve heard it, and I'm not interested in this song.",
+                "Then you can listen to his All the Things You Never Knew, which is very catchy. Both the melody and the lyrics along the movie are very impressive.",
+                "I haven't listened to it before. How is it?",
+                "It's catchy. You can't miss it.",
+                "Sounds good! I wanna listen to it.",
+                "[3] May I play this song for you?",
+                "Sure.",
+                "It's playing for you. Please enjoy it!",
+                "[4] It's a good song. Okay, I need to go now. See you next time.",
+                "All right. Bye!"
+            ],
+            "goal_topic_list": [
+                "Hand in Hand",
+                "Hand in Hand",
+                "Hand in Hand",
+                "Change Me",
+                "Change Me",
+                "All the Things You Never Knew",
+                "All the Things You Never Knew",
+                "All the Things You Never Knew",
+                "All the Things You Never Knew",
+                "All the Things You Never Knew",
+                "All the Things You Never Knew",
+                "All the Things You Never Knew",
+                "Say goodbye",
+                "Say goodbye"
+            ],
+            "goal_type_list": [
+                "Music on demand",
+                "Music on demand",
+                "Music on demand",
+                "Music recommendation",
+                "Music recommendation",
+                "Music recommendation",
+                "Music recommendation",
+                "Music recommendation",
+                "Music recommendation",
+                "Play music",
+                "Play music",
+                "Play music",
+                "Say goodbye",
+                "Say goodbye"
+            ],
+            "situation": "Time: 18:00,on the way home",
+            "knowledge": [
+                [],
+                [],
+                [
+                    "Leehom Wang",
+                    "Sings",
+                    "Hand in Hand"
+                ],
+                [
+                    "Leehom Wang",
+                    "Sings",
+                    "Change Me"
+                ],
+                [],
+                [
+                    "Leehom Wang",
+                    "Sings",
+                    "All the Things You Never Knew"
+                ],
+                [],
+                [],
+                [],
+                [],
+                [],
+                [],
+                [],
+                []
+            ]
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Let's listen to Hand in Hand.",
+                "system response": "It's playing for you. Please enjoy it!",
+                "dialog history": "",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 2,
+                "user utterance": "The songs of Leehom Wang are still so good.",
+                "system response": "Then I recommend that you listen to Change Me, which is also sung by Leehom Wang. It's a song with a rock&roll style. Unlike Leehom Wang's previous works which are exciting and passionate, it starts from the bottom of the heart and finds the emotion in the ordinary with a calm heart.",
+                "dialog history": "<USER> Let's listen to Hand in Hand. <SYSTEM> It's playing for you. Please enjoy it!",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 3,
+                "user utterance": "I\u2018ve heard it, and I'm not interested in this song.",
+                "system response": "Then you can listen to his All the Things You Never Knew, which is very catchy. Both the melody and the lyrics along the movie are very impressive.",
+                "dialog history": "<USER> Let's listen to Hand in Hand. <SYSTEM> It's playing for you. Please enjoy it! <USER> The songs of Leehom Wang are still so good. <SYSTEM> Then I recommend that you listen to Change Me, which is also sung by Leehom Wang. It's a song with a rock&roll style. Unlike Leehom Wang's previous works which are exciting and passionate, it starts from the bottom of the heart and finds the emotion in the ordinary with a calm heart.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 4,
+                "user utterance": "I haven't listened to it before. How is it?",
+                "system response": "It's catchy. You can't miss it.",
+                "dialog history": "<USER> Let's listen to Hand in Hand. <SYSTEM> It's playing for you. Please enjoy it! <USER> The songs of Leehom Wang are still so good. <SYSTEM> Then I recommend that you listen to Change Me, which is also sung by Leehom Wang. It's a song with a rock&roll style. Unlike Leehom Wang's previous works which are exciting and passionate, it starts from the bottom of the heart and finds the emotion in the ordinary with a calm heart. <USER> I\u2018ve heard it, and I'm not interested in this song. <SYSTEM> Then you can listen to his All the Things You Never Knew, which is very catchy. Both the melody and the lyrics along the movie are very impressive.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 5,
+                "user utterance": "Sounds good! I wanna listen to it.",
+                "system response": "May I play this song for you?",
+                "dialog history": "<USER> Let's listen to Hand in Hand. <SYSTEM> It's playing for you. Please enjoy it! <USER> The songs of Leehom Wang are still so good. <SYSTEM> Then I recommend that you listen to Change Me, which is also sung by Leehom Wang. It's a song with a rock&roll style. Unlike Leehom Wang's previous works which are exciting and passionate, it starts from the bottom of the heart and finds the emotion in the ordinary with a calm heart. <USER> I\u2018ve heard it, and I'm not interested in this song. <SYSTEM> Then you can listen to his All the Things You Never Knew, which is very catchy. Both the melody and the lyrics along the movie are very impressive. <USER> I haven't listened to it before. How is it? <SYSTEM> It's catchy. You can't miss it.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 6,
+                "user utterance": "Sure.",
+                "system response": "It's playing for you. Please enjoy it!",
+                "dialog history": "<USER> Let's listen to Hand in Hand. <SYSTEM> It's playing for you. Please enjoy it! <USER> The songs of Leehom Wang are still so good. <SYSTEM> Then I recommend that you listen to Change Me, which is also sung by Leehom Wang. It's a song with a rock&roll style. Unlike Leehom Wang's previous works which are exciting and passionate, it starts from the bottom of the heart and finds the emotion in the ordinary with a calm heart. <USER> I\u2018ve heard it, and I'm not interested in this song. <SYSTEM> Then you can listen to his All the Things You Never Knew, which is very catchy. Both the melody and the lyrics along the movie are very impressive. <USER> I haven't listened to it before. How is it? <SYSTEM> It's catchy. You can't miss it. <USER> Sounds good! I wanna listen to it. <SYSTEM> May I play this song for you?",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 7,
+                "user utterance": "It's a good song. Okay, I need to go now. See you next time.",
+                "system response": "All right. Bye!",
+                "dialog history": "<USER> Let's listen to Hand in Hand. <SYSTEM> It's playing for you. Please enjoy it! <USER> The songs of Leehom Wang are still so good. <SYSTEM> Then I recommend that you listen to Change Me, which is also sung by Leehom Wang. It's a song with a rock&roll style. Unlike Leehom Wang's previous works which are exciting and passionate, it starts from the bottom of the heart and finds the emotion in the ordinary with a calm heart. <USER> I\u2018ve heard it, and I'm not interested in this song. <SYSTEM> Then you can listen to his All the Things You Never Knew, which is very catchy. Both the melody and the lyrics along the movie are very impressive. <USER> I haven't listened to it before. How is it? <SYSTEM> It's catchy. You can't miss it. <USER> Sounds good! I wanna listen to it. <SYSTEM> May I play this song for you? <USER> Sure. <SYSTEM> It's playing for you. Please enjoy it!",
+                "original user side information": {},
+                "original system side information": {}
+            }
+        ]
+    },
+    "DuRecDial-2.0--train--4": {
+        "original dialog id": "",
+        "dialog index": 4,
+        "original dialog info": {
+            "goal": "[1]Ask about weather-->[2] Food recommendation(Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0)-->[3] POI recommendation(Laoqi Sichuan Restaurant)-->[4]Say goodbye",
+            "user_profile": {
+                "Age Range": "26-35",
+                "Name": "Jiaoyang Jin",
+                "Residence": "Xining",
+                "Accepted food": "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0",
+                "Accepted movies": [
+                    "Flash Point",
+                    "Sophie's Revenge",
+                    "I Am Not Madame Bovary",
+                    "Call for Love",
+                    "Hand Phone"
+                ],
+                "Gender": "Female",
+                "Accepted celebrities": [
+                    "Bingbing Fan"
+                ],
+                "Accepted movie": [
+                    "Battle of Wits"
+                ],
+                "Reject": [
+                    "music"
+                ],
+                "Rejected movies": [
+                    "Ever Since We Love"
+                ],
+                "Occupation": "Student",
+                "Favorite news": [
+                    "Bingbing Fan's news"
+                ],
+                "Accepted POI": "Laoqi Sichuan Restaurant"
+            },
+            "conversation": [
+                "[1] Good afternoon. What's the weather like today?",
+                "Today in Xining it is sunny, with northwest winds. The high will be 6 \u2103 and low - 12 \u2103. The temperature is low. Keep warm.",
+                "Okay, I'll be careful. Thank you.",
+                "[2] Hehe. This weather is suitable to eat Saut\u00e9ed Spicy Pork.",
+                "I was thinking about what to eat and then you recommend. You can read my mind.",
+                "Haha. Then don't miss Saut\u00e9ed Spicy Pork.",
+                "I'll have it for lunch.",
+                "[3] I know a place which cooks Saut\u00e9ed Spicy Pork very well, and that is Laoqi Sichuan Restaurant.",
+                "How much does this restaurant cost per person?",
+                "32 yuan.",
+                "It's affordable. What's the address?",
+                "Next to Yinhe Fish, Golden Home, No.914 Qilian Road, Chengbei District. It's easy to find it.",
+                "Okay. I've checked it and it's not very far. What about the ratings?",
+                "4.7 points, very high.",
+                "The score is high. Okay, I'll choose this one. Three of us, at around 1 pm. Would you please make a reservation?",
+                "Okay, I'll do it right now.",
+                "[4] Thank you. I'll go first, bye.",
+                "Okay. Goodbye."
+            ],
+            "goal_topic_list": [
+                "Ask about weather",
+                "Ask about weather",
+                "Ask about weather",
+                "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0",
+                "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0",
+                "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0",
+                "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0",
+                "Laoqi Sichuan Restaurant",
+                "Laoqi Sichuan Restaurant",
+                "Laoqi Sichuan Restaurant",
+                "Laoqi Sichuan Restaurant",
+                "Laoqi Sichuan Restaurant",
+                "Laoqi Sichuan Restaurant",
+                "Laoqi Sichuan Restaurant",
+                "Laoqi Sichuan Restaurant",
+                "Laoqi Sichuan Restaurant",
+                "Say goodbye",
+                "Say goodbye"
+            ],
+            "goal_type_list": [
+                "Ask about weather",
+                "Ask about weather",
+                "Ask about weather",
+                "Food recommendation",
+                "Food recommendation",
+                "Food recommendation",
+                "Food recommendation",
+                "POI recommendation",
+                "POI recommendation",
+                "POI recommendation",
+                "POI recommendation",
+                "POI recommendation",
+                "POI recommendation",
+                "POI recommendation",
+                "POI recommendation",
+                "POI recommendation",
+                "Say goodbye",
+                "Say goodbye"
+            ],
+            "situation": "Time: 20 18 - 11 - 22   12:00, at school   Thursday",
+            "knowledge": [
+                [
+                    "Xining",
+                    "2018-11-22",
+                    "Sunny with northwest winds. The high will be 6 \u2103, and low - 12 \u2103"
+                ],
+                [
+                    "Xining",
+                    "2018-11-22",
+                    "Sunny with northwest winds. The high will be 6 \u2103, and low - 12 \u2103"
+                ],
+                [],
+                [
+                    "Sunny with northwest winds. The high will be 6 \u2103, and low - 12 \u2103",
+                    "Perfect for having",
+                    "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0"
+                ],
+                [],
+                [
+                    "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0",
+                    "Type",
+                    "Hot Dishes"
+                ],
+                [],
+                [
+                    "Laoqi Sichuan Restaurant",
+                    "Specials",
+                    "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0"
+                ],
+                [
+                    "Laoqi Sichuan Restaurant",
+                    "Price per person",
+                    "32"
+                ],
+                [
+                    "Laoqi Sichuan Restaurant",
+                    "Price per person",
+                    "32"
+                ],
+                [
+                    "Laoqi Sichuan Restaurant",
+                    "Address",
+                    "Next to Yinhe Yuzhuang, Jinse Jiayuan, No.914 Qilian Road, Chengbei District"
+                ],
+                [
+                    "Laoqi Sichuan Restaurant",
+                    "Address",
+                    "Next to Yinhe Yuzhuang, Jinse Jiayuan, No.914 Qilian Road, Chengbei District"
+                ],
+                [
+                    "Laoqi Sichuan Restaurant",
+                    "Rating",
+                    "4.7"
+                ],
+                [
+                    "Laoqi Sichuan Restaurant",
+                    "Rating",
+                    "4.7"
+                ],
+                [],
+                [],
+                [],
+                []
+            ]
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Good afternoon. What's the weather like today?",
+                "system response": "Today in Xining it is sunny, with northwest winds. The high will be 6 \u2103 and low - 12 \u2103. The temperature is low. Keep warm.",
+                "dialog history": "",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 2,
+                "user utterance": "Okay, I'll be careful. Thank you.",
+                "system response": "Hehe. This weather is suitable to eat Saut\u00e9ed Spicy Pork.",
+                "dialog history": "<USER> Good afternoon. What's the weather like today? <SYSTEM> Today in Xining it is sunny, with northwest winds. The high will be 6 \u2103 and low - 12 \u2103. The temperature is low. Keep warm.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 3,
+                "user utterance": "I was thinking about what to eat and then you recommend. You can read my mind.",
+                "system response": "Haha. Then don't miss Saut\u00e9ed Spicy Pork.",
+                "dialog history": "<USER> Good afternoon. What's the weather like today? <SYSTEM> Today in Xining it is sunny, with northwest winds. The high will be 6 \u2103 and low - 12 \u2103. The temperature is low. Keep warm. <USER> Okay, I'll be careful. Thank you. <SYSTEM> Hehe. This weather is suitable to eat Saut\u00e9ed Spicy Pork.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 4,
+                "user utterance": "I'll have it for lunch.",
+                "system response": "I know a place which cooks Saut\u00e9ed Spicy Pork very well, and that is Laoqi Sichuan Restaurant.",
+                "dialog history": "<USER> Good afternoon. What's the weather like today? <SYSTEM> Today in Xining it is sunny, with northwest winds. The high will be 6 \u2103 and low - 12 \u2103. The temperature is low. Keep warm. <USER> Okay, I'll be careful. Thank you. <SYSTEM> Hehe. This weather is suitable to eat Saut\u00e9ed Spicy Pork. <USER> I was thinking about what to eat and then you recommend. You can read my mind. <SYSTEM> Haha. Then don't miss Saut\u00e9ed Spicy Pork.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 5,
+                "user utterance": "How much does this restaurant cost per person?",
+                "system response": "32 yuan.",
+                "dialog history": "<USER> Good afternoon. What's the weather like today? <SYSTEM> Today in Xining it is sunny, with northwest winds. The high will be 6 \u2103 and low - 12 \u2103. The temperature is low. Keep warm. <USER> Okay, I'll be careful. Thank you. <SYSTEM> Hehe. This weather is suitable to eat Saut\u00e9ed Spicy Pork. <USER> I was thinking about what to eat and then you recommend. You can read my mind. <SYSTEM> Haha. Then don't miss Saut\u00e9ed Spicy Pork. <USER> I'll have it for lunch. <SYSTEM> I know a place which cooks Saut\u00e9ed Spicy Pork very well, and that is Laoqi Sichuan Restaurant.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 6,
+                "user utterance": "It's affordable. What's the address?",
+                "system response": "Next to Yinhe Fish, Golden Home, No.914 Qilian Road, Chengbei District. It's easy to find it.",
+                "dialog history": "<USER> Good afternoon. What's the weather like today? <SYSTEM> Today in Xining it is sunny, with northwest winds. The high will be 6 \u2103 and low - 12 \u2103. The temperature is low. Keep warm. <USER> Okay, I'll be careful. Thank you. <SYSTEM> Hehe. This weather is suitable to eat Saut\u00e9ed Spicy Pork. <USER> I was thinking about what to eat and then you recommend. You can read my mind. <SYSTEM> Haha. Then don't miss Saut\u00e9ed Spicy Pork. <USER> I'll have it for lunch. <SYSTEM> I know a place which cooks Saut\u00e9ed Spicy Pork very well, and that is Laoqi Sichuan Restaurant. <USER> How much does this restaurant cost per person? <SYSTEM> 32 yuan.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 7,
+                "user utterance": "Okay. I've checked it and it's not very far. What about the ratings?",
+                "system response": "4.7 points, very high.",
+                "dialog history": "<USER> Good afternoon. What's the weather like today? <SYSTEM> Today in Xining it is sunny, with northwest winds. The high will be 6 \u2103 and low - 12 \u2103. The temperature is low. Keep warm. <USER> Okay, I'll be careful. Thank you. <SYSTEM> Hehe. This weather is suitable to eat Saut\u00e9ed Spicy Pork. <USER> I was thinking about what to eat and then you recommend. You can read my mind. <SYSTEM> Haha. Then don't miss Saut\u00e9ed Spicy Pork. <USER> I'll have it for lunch. <SYSTEM> I know a place which cooks Saut\u00e9ed Spicy Pork very well, and that is Laoqi Sichuan Restaurant. <USER> How much does this restaurant cost per person? <SYSTEM> 32 yuan. <USER> It's affordable. What's the address? <SYSTEM> Next to Yinhe Fish, Golden Home, No.914 Qilian Road, Chengbei District. It's easy to find it.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 8,
+                "user utterance": "The score is high. Okay, I'll choose this one. Three of us, at around 1 pm. Would you please make a reservation?",
+                "system response": "Okay, I'll do it right now.",
+                "dialog history": "<USER> Good afternoon. What's the weather like today? <SYSTEM> Today in Xining it is sunny, with northwest winds. The high will be 6 \u2103 and low - 12 \u2103. The temperature is low. Keep warm. <USER> Okay, I'll be careful. Thank you. <SYSTEM> Hehe. This weather is suitable to eat Saut\u00e9ed Spicy Pork. <USER> I was thinking about what to eat and then you recommend. You can read my mind. <SYSTEM> Haha. Then don't miss Saut\u00e9ed Spicy Pork. <USER> I'll have it for lunch. <SYSTEM> I know a place which cooks Saut\u00e9ed Spicy Pork very well, and that is Laoqi Sichuan Restaurant. <USER> How much does this restaurant cost per person? <SYSTEM> 32 yuan. <USER> It's affordable. What's the address? <SYSTEM> Next to Yinhe Fish, Golden Home, No.914 Qilian Road, Chengbei District. It's easy to find it. <USER> Okay. I've checked it and it's not very far. What about the ratings? <SYSTEM> 4.7 points, very high.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 9,
+                "user utterance": "Thank you. I'll go first, bye.",
+                "system response": "Okay. Goodbye.",
+                "dialog history": "<USER> Good afternoon. What's the weather like today? <SYSTEM> Today in Xining it is sunny, with northwest winds. The high will be 6 \u2103 and low - 12 \u2103. The temperature is low. Keep warm. <USER> Okay, I'll be careful. Thank you. <SYSTEM> Hehe. This weather is suitable to eat Saut\u00e9ed Spicy Pork. <USER> I was thinking about what to eat and then you recommend. You can read my mind. <SYSTEM> Haha. Then don't miss Saut\u00e9ed Spicy Pork. <USER> I'll have it for lunch. <SYSTEM> I know a place which cooks Saut\u00e9ed Spicy Pork very well, and that is Laoqi Sichuan Restaurant. <USER> How much does this restaurant cost per person? <SYSTEM> 32 yuan. <USER> It's affordable. What's the address? <SYSTEM> Next to Yinhe Fish, Golden Home, No.914 Qilian Road, Chengbei District. It's easy to find it. <USER> Okay. I've checked it and it's not very far. What about the ratings? <SYSTEM> 4.7 points, very high. <USER> The score is high. Okay, I'll choose this one. Three of us, at around 1 pm. Would you please make a reservation? <SYSTEM> Okay, I'll do it right now.",
+                "original user side information": {},
+                "original system side information": {}
+            }
+        ]
+    },
+    "DuRecDial-2.0--train--5": {
+        "original dialog id": "",
+        "dialog index": 5,
+        "original dialog info": {
+            "goal": "[1]Greetings-->[2]Ask about user's name-->[3]Ask about user's gender-->[4]Ask about user's age-->[5]Ask about user's hobbies-->[6]Say goodbye",
+            "user_profile": {
+                "Residence": "Shijiazhuang",
+                "Gender": "Female",
+                "Age Range": "7-10",
+                "Name": "Xinxi Zhang",
+                "Occupation": "Student"
+            },
+            "conversation": [
+                "[1] Good evening. What are you doing?",
+                "Hello! I'm watching anime.",
+                "How are you doing lately?",
+                "I've stepped backwards in my schoolwork and I've been criticized by my parents today. I'm not happy.",
+                "[2] Then let me talk to you to make you relaxed. What's your name?",
+                "My name is Xinqian Zhang.",
+                "[3] Nice name. Are you a boy or a girl?",
+                "Of course a girl since my name is catchy!",
+                "[4] How old are you this year?",
+                "I'm eight years old.",
+                "[5] What do you like to do?",
+                "Yes, I like small animals, watching animations and listening to children's songs.",
+                "Well your life is colorful.",
+                "[6] I should go to bed early. So bye.",
+                "Okay, see you next time. Bye.",
+                "Bye!"
+            ],
+            "goal_topic_list": [
+                "Greetings",
+                "Greetings",
+                "Greetings",
+                "Greetings",
+                "Ask about user's name",
+                "Ask about user's name",
+                "Ask about user's gender",
+                "Ask about user's gender",
+                "Ask about user's age",
+                "Ask about user's age",
+                "Ask about user's hobbies",
+                "Ask about user's hobbies",
+                "Ask about user's hobbies",
+                "Say goodbye",
+                "Say goodbye",
+                "Say goodbye"
+            ],
+            "goal_type_list": [
+                "Greetings",
+                "Greetings",
+                "Greetings",
+                "Greetings",
+                "Ask about user's name",
+                "Ask about user's name",
+                "Ask about user's gender",
+                "Ask about user's gender",
+                "Ask about user's age",
+                "Ask about user's age",
+                "Ask about user's hobbies",
+                "Ask about user's hobbies",
+                "Ask about user's hobbies",
+                "Say goodbye",
+                "Say goodbye",
+                "Say goodbye"
+            ],
+            "situation": "Time: 20:00, at home Topic: Academic setback",
+            "knowledge": [
+                [],
+                [],
+                [],
+                [],
+                [],
+                [],
+                [],
+                [],
+                [],
+                [],
+                [
+                    "Xinxi Zhang",
+                    "Prefers",
+                    "Animal"
+                ],
+                [
+                    "Xinxi Zhang",
+                    "Prefers",
+                    "Animal"
+                ],
+                [],
+                [],
+                [],
+                []
+            ]
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "",
+                "system response": "Good evening. What are you doing?",
+                "dialog history": "",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 2,
+                "user utterance": "Hello! I'm watching anime.",
+                "system response": "How are you doing lately?",
+                "dialog history": "<SYSTEM> Good evening. What are you doing?",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 3,
+                "user utterance": "I've stepped backwards in my schoolwork and I've been criticized by my parents today. I'm not happy.",
+                "system response": "Then let me talk to you to make you relaxed. What's your name?",
+                "dialog history": "<SYSTEM> Good evening. What are you doing? <USER> Hello! I'm watching anime. <SYSTEM> How are you doing lately?",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 4,
+                "user utterance": "My name is Xinqian Zhang.",
+                "system response": "Nice name. Are you a boy or a girl?",
+                "dialog history": "<SYSTEM> Good evening. What are you doing? <USER> Hello! I'm watching anime. <SYSTEM> How are you doing lately? <USER> I've stepped backwards in my schoolwork and I've been criticized by my parents today. I'm not happy. <SYSTEM> Then let me talk to you to make you relaxed. What's your name?",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 5,
+                "user utterance": "Of course a girl since my name is catchy!",
+                "system response": "How old are you this year?",
+                "dialog history": "<SYSTEM> Good evening. What are you doing? <USER> Hello! I'm watching anime. <SYSTEM> How are you doing lately? <USER> I've stepped backwards in my schoolwork and I've been criticized by my parents today. I'm not happy. <SYSTEM> Then let me talk to you to make you relaxed. What's your name? <USER> My name is Xinqian Zhang. <SYSTEM> Nice name. Are you a boy or a girl?",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 6,
+                "user utterance": "I'm eight years old.",
+                "system response": "What do you like to do?",
+                "dialog history": "<SYSTEM> Good evening. What are you doing? <USER> Hello! I'm watching anime. <SYSTEM> How are you doing lately? <USER> I've stepped backwards in my schoolwork and I've been criticized by my parents today. I'm not happy. <SYSTEM> Then let me talk to you to make you relaxed. What's your name? <USER> My name is Xinqian Zhang. <SYSTEM> Nice name. Are you a boy or a girl? <USER> Of course a girl since my name is catchy! <SYSTEM> How old are you this year?",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 7,
+                "user utterance": "Yes, I like small animals, watching animations and listening to children's songs.",
+                "system response": "Well your life is colorful.",
+                "dialog history": "<SYSTEM> Good evening. What are you doing? <USER> Hello! I'm watching anime. <SYSTEM> How are you doing lately? <USER> I've stepped backwards in my schoolwork and I've been criticized by my parents today. I'm not happy. <SYSTEM> Then let me talk to you to make you relaxed. What's your name? <USER> My name is Xinqian Zhang. <SYSTEM> Nice name. Are you a boy or a girl? <USER> Of course a girl since my name is catchy! <SYSTEM> How old are you this year? <USER> I'm eight years old. <SYSTEM> What do you like to do?",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 8,
+                "user utterance": "I should go to bed early. So bye.",
+                "system response": "Okay, see you next time. Bye.",
+                "dialog history": "<SYSTEM> Good evening. What are you doing? <USER> Hello! I'm watching anime. <SYSTEM> How are you doing lately? <USER> I've stepped backwards in my schoolwork and I've been criticized by my parents today. I'm not happy. <SYSTEM> Then let me talk to you to make you relaxed. What's your name? <USER> My name is Xinqian Zhang. <SYSTEM> Nice name. Are you a boy or a girl? <USER> Of course a girl since my name is catchy! <SYSTEM> How old are you this year? <USER> I'm eight years old. <SYSTEM> What do you like to do? <USER> Yes, I like small animals, watching animations and listening to children's songs. <SYSTEM> Well your life is colorful.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 9,
+                "user utterance": "Bye!",
+                "system response": "",
+                "dialog history": "<SYSTEM> Good evening. What are you doing? <USER> Hello! I'm watching anime. <SYSTEM> How are you doing lately? <USER> I've stepped backwards in my schoolwork and I've been criticized by my parents today. I'm not happy. <SYSTEM> Then let me talk to you to make you relaxed. What's your name? <USER> My name is Xinqian Zhang. <SYSTEM> Nice name. Are you a boy or a girl? <USER> Of course a girl since my name is catchy! <SYSTEM> How old are you this year? <USER> I'm eight years old. <SYSTEM> What do you like to do? <USER> Yes, I like small animals, watching animations and listening to children's songs. <SYSTEM> Well your life is colorful. <USER> I should go to bed early. So bye. <SYSTEM> Okay, see you next time. Bye.",
+                "original user side information": {},
+                "original system side information": {}
+            }
+        ]
+    }
+}

conversational-recommendation-dialogues/DuRecDial-2.0/original_examples.json

@@ -0,0 +1,648 @@
+[
+    {
+        "goal": "[1] Q&A(Cecilia Cheung)-->[2] Chat about stars(Cecilia Cheung)-->[3] Movie recommendation(Failan)-->[4] Movie recommendation(The Stool Pigeon)-->[5]Say goodbye",
+        "user_profile": {
+            "Age Range": "Under 18 years old",
+            "Name": "Fangyang Liu",
+            "Residence": "Qingdao",
+            "Accepted food": "Jiaozi\u00a0Stuffed\u00a0with\u00a0Mackerel\u00a0",
+            "Accepted movies": [
+                "Left Right Love Destiny",
+                "Hot Summer Days",
+                "Fly Me to Polaris",
+                "Help!!!",
+                "One Night in Mongkok",
+                "The Bullet Vanishes"
+            ],
+            "Accepted Music": [
+                "Once"
+            ],
+            "Rejected music": [
+                "It's Time"
+            ],
+            "Gender": "Female",
+            "Accepted celebrities": [
+                "Cecilia Cheung",
+                "Kris Wu",
+                "Nicholas Tse"
+            ],
+            "Accepted movie": [
+                "The Legend of Speed"
+            ],
+            "Reject": [
+                "News"
+            ],
+            "Rejected movies": [
+                "Everyday is Valentine",
+                "Unforgettable",
+                "King of Comedy"
+            ],
+            "Occupation": "Student",
+            "Accepted music": "Time Boils The Rain",
+            "Accepted POI": [
+                "Minguo Seafood Dumpling House"
+            ]
+        },
+        "conversation": [
+            "[1] Who is the leading actor of the movie Left Right Love Destiny?",
+            "It's Cecilia Cheung",
+            "You even know that. Excellent!",
+            "[2] Thank you for your praise. She's a Chinese idol. Of course I know her.",
+            "Yes my idol is quite unusual.",
+            "She is also an Asian Outstanding Artist in New York Chinese Film Festival. Excellent.",
+            "Yes. People like her will shine wherever they go.",
+            "[3] Then don't miss her movie Failan. It shows a love tragedy in which the two people are secluded in different time spaces. However, the movie doesn't just tell a sad but beautiful love story. Through the story, the audiences can see the director's profound thinking and understanding of life and human nature.",
+            "Although I really like her, I prefer to see Nicholas Tse's movies.",
+            "[4] Then you can watch Nicholas Tse's movie The Stool Pigeon. His acting is good.",
+            "What kind of movie is it?",
+            "It's an action drama, with a little bit of thriller.",
+            "Woah, sounds interesting.",
+            "I'm sure you'll like it.",
+            "[5] Then I'm leaving too see the movie.",
+            "Okay, see you next time."
+        ],
+        "goal_topic_list": [
+            "Left Right Love Destiny",
+            "Left Right Love Destiny",
+            "Left Right Love Destiny",
+            "Cecilia Cheung",
+            "Cecilia Cheung",
+            "Cecilia Cheung",
+            "Cecilia Cheung",
+            "Failan",
+            "Failan",
+            "The Stool Pigeon",
+            "The Stool Pigeon",
+            "The Stool Pigeon",
+            "The Stool Pigeon",
+            "The Stool Pigeon",
+            "Say goodbye",
+            "Say goodbye"
+        ],
+        "goal_type_list": [
+            "Q&A",
+            "Q&A",
+            "Q&A",
+            "Chat about stars",
+            "Chat about stars",
+            "Chat about stars",
+            "Chat about stars",
+            "Movie recommendation",
+            "Movie recommendation",
+            "Movie recommendation",
+            "Movie recommendation",
+            "Movie recommendation",
+            "Movie recommendation",
+            "Movie recommendation",
+            "Say goodbye",
+            "Say goodbye"
+        ],
+        "situation": "Time: 12:00, at school",
+        "knowledge": [
+            [
+                "Cecilia Cheung",
+                "Stars",
+                "Left Right Love Destiny"
+            ],
+            [
+                "Cecilia Cheung",
+                "Stars",
+                "Left Right Love Destiny"
+            ],
+            [],
+            [
+                "Cecilia Cheung",
+                "Intro",
+                "Chinese dreamgirl"
+            ],
+            [],
+            [
+                "Cecilia Cheung",
+                "Achievement",
+                "Outstanding Asian artists of New York China Film Festival"
+            ],
+            [],
+            [
+                "Failan",
+                "Comments",
+                "Failan presents a love tragedy isolated in different time and space, but the film does not stop at telling a sad and beautiful love. Through the shell of the sad story, the audience gets the director's deeper thinking and understanding of the human nature of life.Focusing on the spiritual core of saving and being saved, the narrative unfolds, the theme is expounded, and the blindness to reality is unveiled. The audience is touched and awakened. The director fully played the magic of the movie, disrupting the narrative time and space, intersecting the past and the present, and advancing freely following the protagonists\u2019 emotions, making the story structure more tense and the theme and emotions more heartfelt. Although it describes the underworld, the director deliberately avoided the violence rendering and used extremely life-like methods to describe the underworld story routines such as gang struggle and group fight."
+            ],
+            [],
+            [
+                "Nicholas Tse",
+                "Stars",
+                "The Stool Pigeon"
+            ],
+            [
+                "The Stool Pigeon",
+                "Type",
+                "Action plot Thriller"
+            ],
+            [
+                "The Stool Pigeon",
+                "Type",
+                "Action plot Thriller"
+            ],
+            [],
+            [],
+            [],
+            []
+        ]
+    },
+    {
+        "goal": "[1]Ask about weather-->[2] Food recommendation(Marinated Fish)-->[3] POI recommendation(Mr.Fish Roasted)-->[4]Say goodbye",
+        "user_profile": {
+            "Age Range": "Under 18 years old",
+            "Name": "Mingzheng Li",
+            "Residence": "Hengshui",
+            "Accepted food": "Marinated Fish",
+            "Accepted Music": [
+                "You Will Always Be My Love",
+                "After Leaving",
+                "Lingering Memory of Past Love",
+                "Still Think You're the Best",
+                "I Waited Until the Flower Withered",
+                "The Crescent",
+                "Can't Fight The Feeling"
+            ],
+            "Rejected music": [
+                "Coffee",
+                "be torn with grief"
+            ],
+            "Gender": "Male",
+            "Favorite news": [
+                "Jacky Cheung's news"
+            ],
+            "Accepted celebrities": [
+                "Jacky Cheung"
+            ],
+            "Reject": [
+                "Movie"
+            ],
+            "Accepted POI": "Mr.Fish Roasted",
+            "Accepted music": [
+                "Wolf Legend"
+            ],
+            "Occupation": "Student"
+        },
+        "conversation": [
+            "[1] Baby, can you tell me the weather today?",
+            "OK, today in Hengshui it is sunny, with southwest winds. The high will be 4 \u2103 and low - 7 \u2103. Be sure to keep warm.",
+            "Wow, you're great. You know everything. Great!",
+            "[2] There's nothing I don't know. I also know that today's weather is suitable to eat Marinated Fish.",
+            "Okay, I like it.",
+            "I know a restaurant where the Marinated Fish is made of grouper.",
+            "Woah, there's grouper! I really like it! It's a tonic! I really want to have it!",
+            "[3] If you like it so much, I know a restaurant which cooks groupers very well. Mr.Fish Roasted. The Marinated Fish here is very authentic!",
+            "Then tell me about the average meal cost per person, the address and the ratings.",
+            "It costs 0 yuan per person. The address is the intersection of Liushi Road, Huzhuang commercial and residential building, Yingbin North Street, Jizhou District, Jizhou. 5 points, very high.",
+            "Okay. I'll be there tomorrow noon with my partner, taking her to have a taste. Hehe!",
+            "Okay, I'll make a reservation for you. I'll say bon appetite in advance!",
+            "[4] Thanks. Then I'm going to bed first. See you tomorrow. Bye.",
+            "All right. Bye~"
+        ],
+        "goal_topic_list": [
+            "Ask about weather",
+            "Ask about weather",
+            "Ask about weather",
+            "Marinated Fish",
+            "Marinated Fish",
+            "Marinated Fish",
+            "Marinated Fish",
+            "Mr.Fish Roasted",
+            "Mr.Fish Roasted",
+            "Mr.Fish Roasted",
+            "Mr.Fish Roasted",
+            "Mr.Fish Roasted",
+            "Say goodbye",
+            "Say goodbye"
+        ],
+        "goal_type_list": [
+            "Ask about weather",
+            "Ask about weather",
+            "Ask about weather",
+            "Food recommendation",
+            "Food recommendation",
+            "Food recommendation",
+            "Food recommendation",
+            "POI recommendation",
+            "POI recommendation",
+            "POI recommendation",
+            "POI recommendation",
+            "POI recommendation",
+            "Say goodbye",
+            "Say goodbye"
+        ],
+        "situation": "Time: 20 18 - 12 - 12   22:00, at home   Wednesday",
+        "knowledge": [
+            [
+                "Hengshui",
+                "2018-12-12",
+                "Sunny with southwest winds. The high will be 4 \u2103, and low - 7 \u2103"
+            ],
+            [
+                "Hengshui",
+                "2018-12-12",
+                "Sunny with southwest winds. The high will be 4 \u2103, and low - 7 \u2103"
+            ],
+            [],
+            [
+                "Sunny with southwest winds. The high will be 4 \u2103, and low - 7 \u2103",
+                "Perfect for having",
+                "Marinated Fish"
+            ],
+            [],
+            [
+                "Marinated Fish",
+                "Ingredients",
+                "grouper\u3001Olive oil\u3001lemon juice\u3001Garlic\u3001pepper powder\u3001salt"
+            ],
+            [],
+            [
+                "Mr.Fish Roasted",
+                "Specials",
+                "Marinated Fish"
+            ],
+            [
+                "Mr.Fish Roasted",
+                "Rating",
+                "5"
+            ],
+            [
+                "Mr.Fish Roasted",
+                "Rating",
+                "5"
+            ],
+            [],
+            [],
+            [],
+            []
+        ]
+    },
+    {
+        "goal": "[1] Music on demand(Hand in Hand)-->[2] Music recommendation(Change Me)-->[3] Play music(All the Things You Never Knew)-->[4]Say goodbye",
+        "user_profile": {
+            "Residence": "Yangzhou",
+            "Age Range": "Over 50 years old",
+            "Name": "Li Xu",
+            "Accepted food": "Marinated Fish",
+            "Favorite news": [
+                "Bingbing Fan's news",
+                "Leehom Wang's news"
+            ],
+            "Accepted movies": [
+                "Tiles of Deception, Lurid Affections: The Making of 'Lust, Caution'"
+            ],
+            "Accepted Music": [
+                "A Simple Song",
+                "Heroes of Earth"
+            ],
+            "Rejected music": [
+                "KISS GOODBYE"
+            ],
+            "Gender": "Male",
+            "Accepted celebrities": [
+                "Bingbing Fan",
+                "Leehom Wang"
+            ],
+            "Accepted movie": "Flash Point",
+            "Reject": [
+                "Poi"
+            ],
+            "Rejected movies": [
+                "Lust, Caution"
+            ],
+            "Accepted music": [
+                "Hand in Hand"
+            ],
+            "Occupation": "Employed"
+        },
+        "conversation": [
+            "[1] Let's listen to Hand in Hand.",
+            "It's playing for you. Please enjoy it!",
+            "The songs of Leehom Wang are still so good.",
+            "[2] Then I recommend that you listen to Change Me, which is also sung by Leehom Wang. It's a song with a rock&roll style. Unlike Leehom Wang's previous works which are exciting and passionate, it starts from the bottom of the heart and finds the emotion in the ordinary with a calm heart.",
+            "I\u2018ve heard it, and I'm not interested in this song.",
+            "Then you can listen to his All the Things You Never Knew, which is very catchy. Both the melody and the lyrics along the movie are very impressive.",
+            "I haven't listened to it before. How is it?",
+            "It's catchy. You can't miss it.",
+            "Sounds good! I wanna listen to it.",
+            "[3] May I play this song for you?",
+            "Sure.",
+            "It's playing for you. Please enjoy it!",
+            "[4] It's a good song. Okay, I need to go now. See you next time.",
+            "All right. Bye!"
+        ],
+        "goal_topic_list": [
+            "Hand in Hand",
+            "Hand in Hand",
+            "Hand in Hand",
+            "Change Me",
+            "Change Me",
+            "All the Things You Never Knew",
+            "All the Things You Never Knew",
+            "All the Things You Never Knew",
+            "All the Things You Never Knew",
+            "All the Things You Never Knew",
+            "All the Things You Never Knew",
+            "All the Things You Never Knew",
+            "Say goodbye",
+            "Say goodbye"
+        ],
+        "goal_type_list": [
+            "Music on demand",
+            "Music on demand",
+            "Music on demand",
+            "Music recommendation",
+            "Music recommendation",
+            "Music recommendation",
+            "Music recommendation",
+            "Music recommendation",
+            "Music recommendation",
+            "Play music",
+            "Play music",
+            "Play music",
+            "Say goodbye",
+            "Say goodbye"
+        ],
+        "situation": "Time: 18:00,on the way home",
+        "knowledge": [
+            [],
+            [],
+            [
+                "Leehom Wang",
+                "Sings",
+                "Hand in Hand"
+            ],
+            [
+                "Leehom Wang",
+                "Sings",
+                "Change Me"
+            ],
+            [],
+            [
+                "Leehom Wang",
+                "Sings",
+                "All the Things You Never Knew"
+            ],
+            [],
+            [],
+            [],
+            [],
+            [],
+            [],
+            [],
+            []
+        ]
+    },
+    {
+        "goal": "[1]Ask about weather-->[2] Food recommendation(Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0)-->[3] POI recommendation(Laoqi Sichuan Restaurant)-->[4]Say goodbye",
+        "user_profile": {
+            "Age Range": "26-35",
+            "Name": "Jiaoyang Jin",
+            "Residence": "Xining",
+            "Accepted food": "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0",
+            "Accepted movies": [
+                "Flash Point",
+                "Sophie's Revenge",
+                "I Am Not Madame Bovary",
+                "Call for Love",
+                "Hand Phone"
+            ],
+            "Gender": "Female",
+            "Accepted celebrities": [
+                "Bingbing Fan"
+            ],
+            "Accepted movie": [
+                "Battle of Wits"
+            ],
+            "Reject": [
+                "music"
+            ],
+            "Rejected movies": [
+                "Ever Since We Love"
+            ],
+            "Occupation": "Student",
+            "Favorite news": [
+                "Bingbing Fan's news"
+            ],
+            "Accepted POI": "Laoqi Sichuan Restaurant"
+        },
+        "conversation": [
+            "[1] Good afternoon. What's the weather like today?",
+            "Today in Xining it is sunny, with northwest winds. The high will be 6 \u2103 and low - 12 \u2103. The temperature is low. Keep warm.",
+            "Okay, I'll be careful. Thank you.",
+            "[2] Hehe. This weather is suitable to eat Saut\u00e9ed Spicy Pork.",
+            "I was thinking about what to eat and then you recommend. You can read my mind.",
+            "Haha. Then don't miss Saut\u00e9ed Spicy Pork.",
+            "I'll have it for lunch.",
+            "[3] I know a place which cooks Saut\u00e9ed Spicy Pork very well, and that is Laoqi Sichuan Restaurant.",
+            "How much does this restaurant cost per person?",
+            "32 yuan.",
+            "It's affordable. What's the address?",
+            "Next to Yinhe Fish, Golden Home, No.914 Qilian Road, Chengbei District. It's easy to find it.",
+            "Okay. I've checked it and it's not very far. What about the ratings?",
+            "4.7 points, very high.",
+            "The score is high. Okay, I'll choose this one. Three of us, at around 1 pm. Would you please make a reservation?",
+            "Okay, I'll do it right now.",
+            "[4] Thank you. I'll go first, bye.",
+            "Okay. Goodbye."
+        ],
+        "goal_topic_list": [
+            "Ask about weather",
+            "Ask about weather",
+            "Ask about weather",
+            "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0",
+            "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0",
+            "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0",
+            "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0",
+            "Laoqi Sichuan Restaurant",
+            "Laoqi Sichuan Restaurant",
+            "Laoqi Sichuan Restaurant",
+            "Laoqi Sichuan Restaurant",
+            "Laoqi Sichuan Restaurant",
+            "Laoqi Sichuan Restaurant",
+            "Laoqi Sichuan Restaurant",
+            "Laoqi Sichuan Restaurant",
+            "Laoqi Sichuan Restaurant",
+            "Say goodbye",
+            "Say goodbye"
+        ],
+        "goal_type_list": [
+            "Ask about weather",
+            "Ask about weather",
+            "Ask about weather",
+            "Food recommendation",
+            "Food recommendation",
+            "Food recommendation",
+            "Food recommendation",
+            "POI recommendation",
+            "POI recommendation",
+            "POI recommendation",
+            "POI recommendation",
+            "POI recommendation",
+            "POI recommendation",
+            "POI recommendation",
+            "POI recommendation",
+            "POI recommendation",
+            "Say goodbye",
+            "Say goodbye"
+        ],
+        "situation": "Time: 20 18 - 11 - 22   12:00, at school   Thursday",
+        "knowledge": [
+            [
+                "Xining",
+                "2018-11-22",
+                "Sunny with northwest winds. The high will be 6 \u2103, and low - 12 \u2103"
+            ],
+            [
+                "Xining",
+                "2018-11-22",
+                "Sunny with northwest winds. The high will be 6 \u2103, and low - 12 \u2103"
+            ],
+            [],
+            [
+                "Sunny with northwest winds. The high will be 6 \u2103, and low - 12 \u2103",
+                "Perfect for having",
+                "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0"
+            ],
+            [],
+            [
+                "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0",
+                "Type",
+                "Hot Dishes"
+            ],
+            [],
+            [
+                "Laoqi Sichuan Restaurant",
+                "Specials",
+                "Saut\u00e9ed\u00a0Spicy\u00a0Pork\u00a0"
+            ],
+            [
+                "Laoqi Sichuan Restaurant",
+                "Price per person",
+                "32"
+            ],
+            [
+                "Laoqi Sichuan Restaurant",
+                "Price per person",
+                "32"
+            ],
+            [
+                "Laoqi Sichuan Restaurant",
+                "Address",
+                "Next to Yinhe Yuzhuang, Jinse Jiayuan, No.914 Qilian Road, Chengbei District"
+            ],
+            [
+                "Laoqi Sichuan Restaurant",
+                "Address",
+                "Next to Yinhe Yuzhuang, Jinse Jiayuan, No.914 Qilian Road, Chengbei District"
+            ],
+            [
+                "Laoqi Sichuan Restaurant",
+                "Rating",
+                "4.7"
+            ],
+            [
+                "Laoqi Sichuan Restaurant",
+                "Rating",
+                "4.7"
+            ],
+            [],
+            [],
+            [],
+            []
+        ]
+    },
+    {
+        "goal": "[1]Greetings-->[2]Ask about user's name-->[3]Ask about user's gender-->[4]Ask about user's age-->[5]Ask about user's hobbies-->[6]Say goodbye",
+        "user_profile": {
+            "Residence": "Shijiazhuang",
+            "Gender": "Female",
+            "Age Range": "7-10",
+            "Name": "Xinxi Zhang",
+            "Occupation": "Student"
+        },
+        "conversation": [
+            "[1] Good evening. What are you doing?",
+            "Hello! I'm watching anime.",
+            "How are you doing lately?",
+            "I've stepped backwards in my schoolwork and I've been criticized by my parents today. I'm not happy.",
+            "[2] Then let me talk to you to make you relaxed. What's your name?",
+            "My name is Xinqian Zhang.",
+            "[3] Nice name. Are you a boy or a girl?",
+            "Of course a girl since my name is catchy!",
+            "[4] How old are you this year?",
+            "I'm eight years old.",
+            "[5] What do you like to do?",
+            "Yes, I like small animals, watching animations and listening to children's songs.",
+            "Well your life is colorful.",
+            "[6] I should go to bed early. So bye.",
+            "Okay, see you next time. Bye.",
+            "Bye!"
+        ],
+        "goal_topic_list": [
+            "Greetings",
+            "Greetings",
+            "Greetings",
+            "Greetings",
+            "Ask about user's name",
+            "Ask about user's name",
+            "Ask about user's gender",
+            "Ask about user's gender",
+            "Ask about user's age",
+            "Ask about user's age",
+            "Ask about user's hobbies",
+            "Ask about user's hobbies",
+            "Ask about user's hobbies",
+            "Say goodbye",
+            "Say goodbye",
+            "Say goodbye"
+        ],
+        "goal_type_list": [
+            "Greetings",
+            "Greetings",
+            "Greetings",
+            "Greetings",
+            "Ask about user's name",
+            "Ask about user's name",
+            "Ask about user's gender",
+            "Ask about user's gender",
+            "Ask about user's age",
+            "Ask about user's age",
+            "Ask about user's hobbies",
+            "Ask about user's hobbies",
+            "Ask about user's hobbies",
+            "Say goodbye",
+            "Say goodbye",
+            "Say goodbye"
+        ],
+        "situation": "Time: 20:00, at home Topic: Academic setback",
+        "knowledge": [
+            [],
+            [],
+            [],
+            [],
+            [],
+            [],
+            [],
+            [],
+            [],
+            [],
+            [
+                "Xinxi Zhang",
+                "Prefers",
+                "Animal"
+            ],
+            [
+                "Xinxi Zhang",
+                "Prefers",
+                "Animal"
+            ],
+            [],
+            [],
+            [],
+            []
+        ]
+    }
+]

conversational-recommendation-dialogues/OpenDialKG/README.md

@@ -0,0 +1,60 @@
+# OpenDialKG 
+
+OpenDialKG is a dataset of conversations between two crowdsourcing agents engaging in a dialog about a given topic. Each dialog turn is paired with its corresponding “KG paths” that weave together the KG entities and relations that are mentioned in the dialog. More details can be found in the following paper:
+
+Seungwhan Moon, Pararth Shah, Anuj Kumar, Rajen Subba. ["OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs"](https://www.aclweb.org/anthology/P19-1081.pdf), ACL (2019).
+
+## Data Format
+
+The dataset release includes two parts: (1) the Dialog-KG Path Parallel Corpus where each dialog turn is paired with KG paths that connect its previous turn (annotated by chat participants themselves), and (2) the base knowledge graph used in both the dialog collection and in the experiments, which is a subset of the [Freebase Easy data](http://freebase-easy.cs.uni-freiburg.de/dump/). The data are made available in the following files:
+```
+[Dialog-KG Parallel Corpus]
+- ./data/opendialkg.csv
+
+[KG]
+- ./data/opendialkg_entities.txt
+- ./data/opendialkg_relations.txt
+- ./data/opendialkg_triples.txt 
+```
+
+The Dialog-KG Parallel Corpus (`./data/opendialkg.csv`) is formatted as a csv file, where columns are: `Messages, User Rating, Assistant Rating`. Each row refers to a dialog session, which is a JSON-formatted `<list>` of each action formatted as follows::
+```
+{
+	"type": // <str> indicating whether it's a message ("chat") or a KG walk selection action ("action")
+	"sender": // <str> indicating indicating whether it is sent by "user" or "assistant"
+	"message" (Optional): // <str> raw utterance (for "type": "chat"),
+	"metadata" (Optional): {
+		"path": [
+			<float> // path score,
+			<list> // of KG triples (subject, relation, object) that make up the path,
+			<str> // rendering of the path
+		]
+	} // end of KG path JSON (if available)
+}. ... // end of each action JSON
+```
+
+Note that the path annotation refers to the connection of two adjacent turns on the conceptual level. Given `utterance_1`, `utterance_2`, and their annotated entity path `A -> B -> C` that connect `utterance_1` and `utterance_2`, Entity `A` is assumed to be mentioned in `utterance_1`, and `C` to be mentioned in `utterance_2`. Entity `B` doesn't necessarily have to be mentioned since it is an intermediate step in the path. Note also that it is a paraphrased dataset, thus each mention is not enforced to have an exact surface match with its corresponding entity in the knowledge graph. After pre-processing and quality reviews we release the 13,802 dialog sessions (91,209 turns) across two tasks (Chit-chat and Recommendations) and four domains (movie, book, sports, and music).
+
+All bi-directional KG triples used in the dataset collection and in the experiments (100,813 entities, 1358 relations, 1,190,658 triples) are included in `./data/opendialkg_triples.txt`, formatted as line-separated triples with tab-separated entities and relations:
+```
+subject \t relation \t object \n
+...
+```
+
+All entities and relations are also listed in `./data/opendialkg_entities.txt` and `./data/opendialkg_relations.txt`, respectively. The prefix `~` in `opendialkg_relations.txt` refers to reverse relations.
+
+## Reference
+
+To cite this work please use:
+```
+@InProceedings{Moon2019opendialkg,
+author = {Seungwhan Moon and Pararth Shah and Anuj Kumar and Rajen Subba},
+title = {OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs},
+booktitle = {Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics},
+month = {July},
+year = {2019},
+}
+```
+
+## License
+OpenDialKG is released under [CC-BY-NC-4.0](https://creativecommons.org/licenses/by-nc/4.0/legalcode), see [LICENSE](LICENSE) for details.

conversational-recommendation-dialogues/OpenDialKG/converted_examples.json

@@ -0,0 +1,450 @@
+{
+    "OpenDialKG--train--1": {
+        "original dialog id": "",
+        "dialog index": 1,
+        "original dialog info": {
+            "User Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}",
+            "Assistant Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}"
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Do you like Iron Man",
+                "system response": "Sure do! Robert Downey Jr. is a favorite.",
+                "dialog history": "",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat",
+                    "metadata": {
+                        "metadata": {
+                            "path": [
+                                0.0,
+                                [
+                                    [
+                                        "Iron Man",
+                                        "starred_actors",
+                                        "Robert Downey Jr."
+                                    ]
+                                ],
+                                "Iron Man is starring Robert Downey Jr."
+                            ]
+                        },
+                        "type": "action",
+                        "sender": "assistant",
+                        "action_id": "kgwalk/choose_path"
+                    }
+                }
+            },
+            {
+                "turn id": 2,
+                "user utterance": "Yes i like him too did you know he also was in Zodiac a crime fiction film.",
+                "system response": "I like crime fiction! Didn't know RDJ was in there. Jake Gyllenhaal starred as well.",
+                "dialog history": "<USER> Do you like Iron Man <SYSTEM> Sure do! Robert Downey Jr. is a favorite.",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat",
+                    "metadata": {
+                        "metadata": {
+                            "path": [
+                                0.0,
+                                [
+                                    [
+                                        "Zodiac (Crime Fiction Film)",
+                                        "starred_actors",
+                                        "Jake Gyllenhaal"
+                                    ]
+                                ],
+                                "Zodiac (Crime Fiction Film) is starring Jake Gyllenhaal"
+                            ]
+                        },
+                        "type": "action",
+                        "sender": "assistant",
+                        "action_id": "kgwalk/choose_path"
+                    }
+                }
+            },
+            {
+                "turn id": 3,
+                "user utterance": "So he did he also starred in End of Watch have you ever seen that movie?",
+                "system response": "Yes I have! I like films directed by David Ayer. How about you?",
+                "dialog history": "<USER> Do you like Iron Man <SYSTEM> Sure do! Robert Downey Jr. is a favorite. <USER> Yes i like him too did you know he also was in Zodiac a crime fiction film. <SYSTEM> I like crime fiction! Didn't know RDJ was in there. Jake Gyllenhaal starred as well.",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat",
+                    "metadata": {
+                        "metadata": {
+                            "path": [
+                                3.0,
+                                [
+                                    [
+                                        "End of Watch",
+                                        "has_genre",
+                                        "Thriller"
+                                    ]
+                                ],
+                                "End of Watch has genre Thriller"
+                            ]
+                        },
+                        "type": "action",
+                        "sender": "assistant",
+                        "action_id": "kgwalk/choose_path"
+                    }
+                }
+            },
+            {
+                "turn id": 4,
+                "user utterance": "I have not what genre is End of Watch",
+                "system response": "It's a thriller and crime fiction as well.",
+                "dialog history": "<USER> Do you like Iron Man <SYSTEM> Sure do! Robert Downey Jr. is a favorite. <USER> Yes i like him too did you know he also was in Zodiac a crime fiction film. <SYSTEM> I like crime fiction! Didn't know RDJ was in there. Jake Gyllenhaal starred as well. <USER> So he did he also starred in End of Watch have you ever seen that movie? <SYSTEM> Yes I have! I like films directed by David Ayer. How about you?",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat"
+                }
+            },
+            {
+                "turn id": 5,
+                "user utterance": "I will make sure to check it out I like thrillers thank you",
+                "system response": "Welcome!",
+                "dialog history": "<USER> Do you like Iron Man <SYSTEM> Sure do! Robert Downey Jr. is a favorite. <USER> Yes i like him too did you know he also was in Zodiac a crime fiction film. <SYSTEM> I like crime fiction! Didn't know RDJ was in there. Jake Gyllenhaal starred as well. <USER> So he did he also starred in End of Watch have you ever seen that movie? <SYSTEM> Yes I have! I like films directed by David Ayer. How about you? <USER> I have not what genre is End of Watch <SYSTEM> It's a thriller and crime fiction as well.",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat"
+                }
+            }
+        ]
+    },
+    "OpenDialKG--train--2": {
+        "original dialog id": "",
+        "dialog index": 2,
+        "original dialog info": {
+            "User Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}",
+            "Assistant Rating": "{\"dialog_rating\": \"3\", \"other_agent_rating\": \"3\"}"
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Could you recommend any books like The Secret Life of Bees?",
+                "system response": "Yes, its a great teen book, have you heard about A walk to remember ? It is also a great teen drama",
+                "dialog history": "",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat",
+                    "metadata": {
+                        "metadata": {
+                            "path": [
+                                -1.5,
+                                [
+                                    [
+                                        "The Secret Life of Bees",
+                                        "has_genre",
+                                        "Teen drama"
+                                    ],
+                                    [
+                                        "Teen drama",
+                                        "~has_genre",
+                                        "A Walk to Remember"
+                                    ]
+                                ],
+                                "The Secret Life of Bees has genre Teen drama. Teen drama has examples: A Walk to Remember"
+                            ]
+                        },
+                        "type": "action",
+                        "sender": "assistant",
+                        "action_id": "kgwalk/choose_path"
+                    }
+                }
+            },
+            {
+                "turn id": 2,
+                "user utterance": "I think I have.. is that one with Hunt Lowry?",
+                "system response": "yes and he also produced White Oleander and it was released in 1999",
+                "dialog history": "<USER> Could you recommend any books like The Secret Life of Bees? <SYSTEM> Yes, its a great teen book, have you heard about A walk to remember ? It is also a great teen drama",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat",
+                    "metadata": {
+                        "metadata": {
+                            "path": [
+                                -2,
+                                [
+                                    [
+                                        "Hunt Lowry",
+                                        "~Produced by",
+                                        "A Walk to Remember"
+                                    ],
+                                    [
+                                        "A Walk to Remember",
+                                        "is-a",
+                                        "Film"
+                                    ]
+                                ],
+                                "Hunt Lowry produced A Walk to Remember. A Walk to Remember is a/an Film"
+                            ]
+                        },
+                        "type": "action",
+                        "sender": "assistant",
+                        "action_id": "kgwalk/choose_path"
+                    }
+                }
+            },
+            {
+                "turn id": 3,
+                "user utterance": "Oh, awesome. What genre is that film?",
+                "system response": "It is film adaption with a melodrama. Do you like Drama movies?",
+                "dialog history": "<USER> Could you recommend any books like The Secret Life of Bees? <SYSTEM> Yes, its a great teen book, have you heard about A walk to remember ? It is also a great teen drama <USER> I think I have.. is that one with Hunt Lowry? <SYSTEM> yes and he also produced White Oleander and it was released in 1999",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat"
+                }
+            },
+            {
+                "turn id": 4,
+                "user utterance": "Great! I love drama movies. I'll check this one out then. Thanks so much!",
+                "system response": "Cool, hope you enjoy. any m ore recommendations you want ?",
+                "dialog history": "<USER> Could you recommend any books like The Secret Life of Bees? <SYSTEM> Yes, its a great teen book, have you heard about A walk to remember ? It is also a great teen drama <USER> I think I have.. is that one with Hunt Lowry? <SYSTEM> yes and he also produced White Oleander and it was released in 1999 <USER> Oh, awesome. What genre is that film? <SYSTEM> It is film adaption with a melodrama. Do you like Drama movies?",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat"
+                }
+            },
+            {
+                "turn id": 5,
+                "user utterance": "Whoops, I meant books. I love Drama books! And no, I think that's good. Thanks for your help.",
+                "system response": "You are welcome",
+                "dialog history": "<USER> Could you recommend any books like The Secret Life of Bees? <SYSTEM> Yes, its a great teen book, have you heard about A walk to remember ? It is also a great teen drama <USER> I think I have.. is that one with Hunt Lowry? <SYSTEM> yes and he also produced White Oleander and it was released in 1999 <USER> Oh, awesome. What genre is that film? <SYSTEM> It is film adaption with a melodrama. Do you like Drama movies? <USER> Great! I love drama movies. I'll check this one out then. Thanks so much! <SYSTEM> Cool, hope you enjoy. any m ore recommendations you want ?",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat",
+                    "metadata": {
+                        "metadata": {
+                            "text": "only you can end this dialouge"
+                        },
+                        "type": "action",
+                        "sender": "assistant",
+                        "action_id": "meta_thread/send_meta_message"
+                    }
+                }
+            }
+        ]
+    },
+    "OpenDialKG--train--3": {
+        "original dialog id": "",
+        "dialog index": 3,
+        "original dialog info": {
+            "User Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}",
+            "Assistant Rating": "{\"dialog_rating\": \"4\", \"other_agent_rating\": \"5\"}"
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Could you recommend any books by Ken Kesey?",
+                "system response": "Yes, he wrote One Flew Over the Cuckoo's Nest",
+                "dialog history": "",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat"
+                }
+            },
+            {
+                "turn id": 2,
+                "user utterance": "Isn't that a movie too?",
+                "system response": "Yes it sure was it was released in 1975",
+                "dialog history": "<USER> Could you recommend any books by Ken Kesey? <SYSTEM> Yes, he wrote One Flew Over the Cuckoo's Nest",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat"
+                }
+            },
+            {
+                "turn id": 3,
+                "user utterance": "Who was in that?",
+                "system response": "In the movie there was Jack Nicholson ,Louise Fletcher",
+                "dialog history": "<USER> Could you recommend any books by Ken Kesey? <SYSTEM> Yes, he wrote One Flew Over the Cuckoo's Nest <USER> Isn't that a movie too? <SYSTEM> Yes it sure was it was released in 1975",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat"
+                }
+            }
+        ]
+    },
+    "OpenDialKG--train--4": {
+        "original dialog id": "",
+        "dialog index": 4,
+        "original dialog info": {
+            "User Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}",
+            "Assistant Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}"
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Do you like Michael Jackson?",
+                "system response": "I do he was very talented and an all around performer. He wrote Dancing on the Dream which is one of my favorites.",
+                "dialog history": "",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat",
+                    "metadata": {
+                        "metadata": {
+                            "path": [
+                                -0.5,
+                                [
+                                    [
+                                        "Michael Jackson",
+                                        "~written_by",
+                                        "Dancing the Dream"
+                                    ]
+                                ],
+                                "Michael Jackson wrote Dancing the Dream"
+                            ]
+                        },
+                        "type": "action",
+                        "sender": "assistant",
+                        "action_id": "kgwalk/choose_path"
+                    }
+                }
+            },
+            {
+                "turn id": 2,
+                "user utterance": "Yes, he was very talented indeed. He also won Grammy of the Year, possibly more than once",
+                "system response": "Yes, Healing the World is one of my favorite songs and the music video was very touching.",
+                "dialog history": "<USER> Do you like Michael Jackson? <SYSTEM> I do he was very talented and an all around performer. He wrote Dancing on the Dream which is one of my favorites.",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat",
+                    "metadata": {
+                        "metadata": {
+                            "path": [
+                                -1,
+                                [
+                                    [
+                                        "Michael Jackson",
+                                        "~Lyricist",
+                                        "Heal the World"
+                                    ]
+                                ],
+                                "Michael Jackson : `~Lyricist`: Heal the World"
+                            ]
+                        },
+                        "type": "action",
+                        "sender": "assistant",
+                        "action_id": "kgwalk/choose_path"
+                    }
+                }
+            },
+            {
+                "turn id": 3,
+                "user utterance": "Have you ever seen footage of him from a young age. He was such a gifted child",
+                "system response": "Yes, when he was in Jackson 5. He was on Motown Records",
+                "dialog history": "<USER> Do you like Michael Jackson? <SYSTEM> I do he was very talented and an all around performer. He wrote Dancing on the Dream which is one of my favorites. <USER> Yes, he was very talented indeed. He also won Grammy of the Year, possibly more than once <SYSTEM> Yes, Healing the World is one of my favorite songs and the music video was very touching.",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat"
+                }
+            }
+        ]
+    },
+    "OpenDialKG--train--5": {
+        "original dialog id": "",
+        "dialog index": 5,
+        "original dialog info": {
+            "User Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}",
+            "Assistant Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}"
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Could you recommend books similar to Dead to the World?",
+                "system response": "Do you like this book because of it's author Charlaine Harris?",
+                "dialog history": "",
+                "original user side information": {
+                    "type": "chat",
+                    "metadata": {
+                        "metadata": {
+                            "text": "sure"
+                        },
+                        "type": "action",
+                        "sender": "user",
+                        "action_id": "meta_thread/send_meta_message"
+                    }
+                },
+                "original system side information": {
+                    "type": "chat"
+                }
+            },
+            {
+                "turn id": 2,
+                "user utterance": "Yes. What other books did she write?",
+                "system response": "A popular book of her's is the Southern Vampire Mysteries",
+                "dialog history": "<USER> Could you recommend books similar to Dead to the World? <SYSTEM> Do you like this book because of it's author Charlaine Harris?",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat",
+                    "metadata": {
+                        "metadata": {
+                            "path": [
+                                0.0,
+                                [
+                                    [
+                                        "The Southern Vampire Mysteries",
+                                        "written_by",
+                                        "Charlaine Harris"
+                                    ]
+                                ],
+                                "The Southern Vampire Mysteries is written by Charlaine Harris"
+                            ]
+                        },
+                        "type": "action",
+                        "sender": "assistant",
+                        "action_id": "kgwalk/choose_path"
+                    }
+                }
+            },
+            {
+                "turn id": 3,
+                "user utterance": "Thanks for that. I will check out Southern Vampire Mysteries!",
+                "system response": "Sure thing, hope you enjoy",
+                "dialog history": "<USER> Could you recommend books similar to Dead to the World? <SYSTEM> Do you like this book because of it's author Charlaine Harris? <USER> Yes. What other books did she write? <SYSTEM> A popular book of her's is the Southern Vampire Mysteries",
+                "original user side information": {
+                    "type": "chat"
+                },
+                "original system side information": {
+                    "type": "chat"
+                }
+            }
+        ]
+    }
+}

conversational-recommendation-dialogues/OpenDialKG/original_examples.json

@@ -0,0 +1,27 @@
+[
+    {
+        "Messages": "[{\"message\": \"Do you like Iron Man\", \"type\": \"chat\", \"sender\": \"user\"}, {\"metadata\": {\"path\": [0.0, [[\"Iron Man\", \"starred_actors\", \"Robert Downey Jr.\"]], \"Iron Man is starring Robert Downey Jr.\"]}, \"type\": \"action\", \"sender\": \"assistant\", \"action_id\": \"kgwalk/choose_path\"}, {\"message\": \"Sure do! Robert Downey Jr. is a favorite.\", \"type\": \"chat\", \"sender\": \"assistant\"}, {\"metadata\": {\"path\": [-0.5, [[\"Robert Downey Jr.\", \"~starred_actors\", \"Zodiac (Crime Fiction Film)\"]], \"Robert Downey Jr. starred in Zodiac (Crime Fiction Film)\"]}, \"type\": \"action\", \"sender\": \"user\", \"action_id\": \"kgwalk/choose_path\"}, {\"message\": \"Yes i like him too did you know he also was in Zodiac a crime fiction film.\", \"type\": \"chat\", \"sender\": \"user\"}, {\"metadata\": {\"path\": [0.0, [[\"Zodiac (Crime Fiction Film)\", \"starred_actors\", \"Jake Gyllenhaal\"]], \"Zodiac (Crime Fiction Film) is starring Jake Gyllenhaal\"]}, \"type\": \"action\", \"sender\": \"assistant\", \"action_id\": \"kgwalk/choose_path\"}, {\"message\": \"I like crime fiction! Didn't know RDJ was in there. Jake Gyllenhaal starred as well.\", \"type\": \"chat\", \"sender\": \"assistant\"}, {\"metadata\": {\"path\": [0.0, [[\"Jake Gyllenhaal\", \"~starred_actors\", \"End of Watch\"], [\"End of Watch\", \"written_by\", \"David Ayer\"]], \"Jake Gyllenhaal starred in End of Watch. End of Watch is written by David Ayer\"]}, \"type\": \"action\", \"sender\": \"user\", \"action_id\": \"kgwalk/choose_path\"}, {\"message\": \"So he did he also starred in End of Watch have you ever seen that movie?\", \"type\": \"chat\", \"sender\": \"user\"}, {\"metadata\": {\"path\": [3.0, [[\"End of Watch\", \"has_genre\", \"Thriller\"]], \"End of Watch has genre Thriller\"]}, \"type\": \"action\", \"sender\": \"assistant\", \"action_id\": \"kgwalk/choose_path\"}, {\"message\": \"Yes I have! I like films directed by David Ayer. How about you?\", \"type\": \"chat\", \"sender\": \"assistant\"}, {\"message\": \"I have not what genre is End of Watch\", \"type\": \"chat\", \"sender\": \"user\"}, {\"message\": \"It's a thriller and crime fiction as well.\", \"type\": \"chat\", \"sender\": \"assistant\"}, {\"message\": \"I will make sure to check it out I like thrillers thank you\", \"type\": \"chat\", \"sender\": \"user\"}, {\"message\": \"Welcome!\", \"type\": \"chat\", \"sender\": \"assistant\"}]",
+        "User Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}",
+        "Assistant Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}"
+    },
+    {
+        "Messages": "[{\"message\": \"Could you recommend any books like The Secret Life of Bees?\", \"type\": \"chat\", \"sender\": \"user\"}, {\"metadata\": {\"path\": [-1.5, [[\"The Secret Life of Bees\", \"has_genre\", \"Teen drama\"], [\"Teen drama\", \"~has_genre\", \"A Walk to Remember\"]], \"The Secret Life of Bees has genre Teen drama. Teen drama has examples: A Walk to Remember\"]}, \"type\": \"action\", \"sender\": \"assistant\", \"action_id\": \"kgwalk/choose_path\"}, {\"message\": \"Yes, its a great teen book, have you heard about A walk to remember ? It is also a great teen drama\", \"type\": \"chat\", \"sender\": \"assistant\"}, {\"metadata\": {\"path\": [1.0, [[\"A Walk to Remember\", \"Produced by\", \"Hunt Lowry\"]], \"A Walk to Remember is produced by Hunt Lowry\"]}, \"type\": \"action\", \"sender\": \"user\", \"action_id\": \"kgwalk/choose_path\"}, {\"message\": \"I think I have.. is that one with Hunt Lowry?\", \"type\": \"chat\", \"sender\": \"user\"}, {\"metadata\": {\"path\": [-2, [[\"Hunt Lowry\", \"~Produced by\", \"A Walk to Remember\"], [\"A Walk to Remember\", \"is-a\", \"Film\"]], \"Hunt Lowry produced A Walk to Remember. A Walk to Remember is a/an Film\"]}, \"type\": \"action\", \"sender\": \"assistant\", \"action_id\": \"kgwalk/choose_path\"}, {\"message\": \"yes and he also produced White Oleander and it was released in 1999\", \"type\": \"chat\", \"sender\": \"assistant\"}, {\"message\": \"Oh, awesome. What genre is that film?\", \"type\": \"chat\", \"sender\": \"user\"}, {\"message\": \"It is film adaption with a melodrama. Do you like Drama movies?\", \"type\": \"chat\", \"sender\": \"assistant\"}, {\"message\": \"Great! I love drama movies. I'll check this one out then. Thanks so much!\", \"type\": \"chat\", \"sender\": \"user\"}, {\"message\": \"Cool, hope you enjoy. any m ore recommendations you want ?\", \"type\": \"chat\", \"sender\": \"assistant\"}, {\"message\": \"Whoops, I meant books. I love Drama books! And no, I think that's good. Thanks for your help.\", \"type\": \"chat\", \"sender\": \"user\"}, {\"metadata\": {\"text\": \"only you can end this dialouge\"}, \"type\": \"action\", \"sender\": \"assistant\", \"action_id\": \"meta_thread/send_meta_message\"}, {\"message\": \"You are welcome\", \"type\": \"chat\", \"sender\": \"assistant\"}]",
+        "User Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}",
+        "Assistant Rating": "{\"dialog_rating\": \"3\", \"other_agent_rating\": \"3\"}"
+    },
+    {
+        "Messages": "[{\"message\": \"Could you recommend any books by Ken Kesey?\", \"type\": \"chat\", \"sender\": \"user\"}, {\"message\": \"Yes, he wrote One Flew Over the Cuckoo's Nest\", \"type\": \"chat\", \"sender\": \"assistant\"}, {\"message\": \"Isn't that a movie too?\", \"type\": \"chat\", \"sender\": \"user\"}, {\"message\": \"Yes it sure was it was released in 1975\", \"type\": \"chat\", \"sender\": \"assistant\"}, {\"message\": \"Who was in that?\", \"type\": \"chat\", \"sender\": \"user\"}, {\"message\": \"In the movie there was Jack Nicholson ,Louise Fletcher \", \"type\": \"chat\", \"sender\": \"assistant\"}]",
+        "User Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}",
+        "Assistant Rating": "{\"dialog_rating\": \"4\", \"other_agent_rating\": \"5\"}"
+    },
+    {
+        "Messages": "[{\"message\": \"Do you like Michael Jackson?\", \"type\": \"chat\", \"sender\": \"user\"}, {\"metadata\": {\"path\": [-0.5, [[\"Michael Jackson\", \"~written_by\", \"Dancing the Dream\"]], \"Michael Jackson wrote Dancing the Dream\"]}, \"type\": \"action\", \"sender\": \"assistant\", \"action_id\": \"kgwalk/choose_path\"}, {\"message\": \"I do he was very talented and an all around performer. He wrote Dancing on the Dream which is one of my favorites. \", \"type\": \"chat\", \"sender\": \"assistant\"}, {\"metadata\": {\"path\": [-2, [[\"Dancing the Dream\", \"written_by\", \"Michael Jackson\"], [\"Michael Jackson\", \"Award Won\", \"Grammy Award for Album of the Year\"]], \"Dancing the Dream is written by Michael Jackson. Michael Jackson : `Award Won`: Grammy Award for Album of the Year\"]}, \"type\": \"action\", \"sender\": \"user\", \"action_id\": \"kgwalk/choose_path\"}, {\"message\": \"Yes, he was very talented indeed. He also won Grammy of the Year, possibly more than once\", \"type\": \"chat\", \"sender\": \"user\"}, {\"metadata\": {\"path\": [-1, [[\"Michael Jackson\", \"~Lyricist\", \"Heal the World\"]], \"Michael Jackson : `~Lyricist`: Heal the World\"]}, \"type\": \"action\", \"sender\": \"assistant\", \"action_id\": \"kgwalk/choose_path\"}, {\"message\": \"Yes, Healing the World is one of my favorite songs and the music video was very touching.\", \"type\": \"chat\", \"sender\": \"assistant\"}, {\"message\": \"Have you ever seen footage of him from a young age. He was such a gifted child\", \"type\": \"chat\", \"sender\": \"user\"}, {\"message\": \"Yes, when he was in Jackson 5. He was on Motown Records \", \"type\": \"chat\", \"sender\": \"assistant\"}, {\"message\": \"Yes, I love those classic hits! Like I want you back.\", \"type\": \"chat\", \"sender\": \"user\"}]",
+        "User Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}",
+        "Assistant Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}"
+    },
+    {
+        "Messages": "[{\"message\": \"Could you recommend books similar to Dead to the World?\", \"type\": \"chat\", \"sender\": \"user\"}, {\"metadata\": {\"path\": [0.0, [[\"Dead to the World\", \"written_by\", \"Charlaine Harris\"]], \"Dead to the World is written by Charlaine Harris\"]}, \"type\": \"action\", \"sender\": \"assistant\", \"action_id\": \"kgwalk/choose_path\"}, {\"metadata\": {\"text\": \"I need a little more time please\"}, \"type\": \"action\", \"sender\": \"assistant\", \"action_id\": \"meta_thread/send_meta_message\"}, {\"metadata\": {\"text\": \"sure\"}, \"type\": \"action\", \"sender\": \"user\", \"action_id\": \"meta_thread/send_meta_message\"}, {\"message\": \"Do you like this book because of it's author Charlaine Harris?\", \"type\": \"chat\", \"sender\": \"assistant\"}, {\"metadata\": {\"path\": [-0.5, [[\"Charlaine Harris\", \"~written_by\", \"The Southern Vampire Mysteries\"]], \"Charlaine Harris wrote The Southern Vampire Mysteries\"]}, \"type\": \"action\", \"sender\": \"user\", \"action_id\": \"kgwalk/choose_path\"}, {\"message\": \"Yes. What other books did she write?\", \"type\": \"chat\", \"sender\": \"user\"}, {\"metadata\": {\"path\": [0.0, [[\"The Southern Vampire Mysteries\", \"written_by\", \"Charlaine Harris\"]], \"The Southern Vampire Mysteries is written by Charlaine Harris\"]}, \"type\": \"action\", \"sender\": \"assistant\", \"action_id\": \"kgwalk/choose_path\"}, {\"message\": \"A popular book of her's is the Southern Vampire Mysteries\", \"type\": \"chat\", \"sender\": \"assistant\"}, {\"message\": \"Thanks for that. I will check out Southern Vampire Mysteries!\", \"type\": \"chat\", \"sender\": \"user\"}, {\"message\": \"Sure thing, hope you enjoy\", \"type\": \"chat\", \"sender\": \"assistant\"}]",
+        "User Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}",
+        "Assistant Rating": "{\"dialog_rating\": \"5\", \"other_agent_rating\": \"5\"}"
+    }
+]

conversational-recommendation-dialogues/README.md

@@ -0,0 +1,79 @@
+### Conversational Recommendation Dialogues
+
+Conversational Recommendation Dialogues follow same format as task oriented dialogues. Below is the copy of ReadME from task oriented dialogues:
+
+Below is a general format for task oriented dialogues:
+
+```js
+{
+    "dataset_name--train/val/test--dialog_id": {
+        "original dialog id": str,
+        "dialog index": int,
+        "original dialog info": dict,
+        "log": [
+            {
+                "turn id": int,
+                "user utterance": str,
+                "system response": str,
+                "dialog history": str,
+                "original user side information": dict,
+                "original system side information": dict,
+                "dst": str,
+                "dst accumulated": str
+            },
+         	...
+        ],
+        "external knowledge non-flat": {
+            "metadata": dict,
+            "slots and values": dict
+            "intents": dict,
+            ...
+        },
+        "external knowledge": str,
+        "intent knowledge": str,
+        "prompt": [
+            "This is a bot helping users to get navigation. Given the dialog context and external database, please generate a relevant system response for the user.",
+            ...
+        ]
+    },
+    ...
+}
+```
+
+In general, datasets have the "external knowledge non-flat" and "external knowledge"  in the whole dialogue level. There are also some datasets where every turn in "log" has own "external knowledge non-flat" and "external knowledge". 
+
+Here are datasets with turn-level "external knowledge": 
+```
+'SimJointGEN', 'BiTOD', 'OpenDialKG', 'SimJointMovie', 'MS-DC', 'STAR', 'SimJointRestaurant', 'Taskmaster1', 'Taskmaster2', 'Taskmaster3'
+```
+And below is a general format for such datasets:
+```js
+{
+    "dataset_name--train/val/test--dialog_id": {
+        "original dialog id": str,
+        "dialog index": int,
+        "original dialog info": dict,
+        "log": [
+            {
+                "turn id": int,
+                "user utterance": str,
+                "system response": str,
+                "dialog history": str,
+                "original user side information": dict,
+                "original system side information": dict,
+                "dst": str,
+                "dst accumulated": str
+                "external knowledge non-flat": list,
+                "external knowledge": str,
+            },
+         	...
+        ]
+        "prompt": [
+            "This is a bot helping users to get navigation. Given the dialog context and external database, please generate a relevant system response for the user.",
+            ...
+        ]
+    },
+    ...
+}
+```
+Please refer to each dataset folder for more details.

conversational-recommendation-dialogues/Redial/converted_examples.json

@@ -0,0 +1,954 @@
+{
+    "Redial--train--1": {
+        "original dialog id": "391",
+        "dialog index": 1,
+        "original dialog info": {
+            "movieMentions": {
+                "203371": "Final Fantasy: The Spirits Within (2001)",
+                "84779": "The Triplets of Belleville (2003)",
+                "122159": "Mary and Max (2009)",
+                "151313": "A Scanner Darkly  (2006)",
+                "191602": "Waking Life (2001)",
+                "165710": "The Boss Baby (2017)"
+            },
+            "respondentQuestions": {
+                "203371": {
+                    "suggested": 1,
+                    "seen": 0,
+                    "liked": 1
+                },
+                "84779": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "122159": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "151313": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "191602": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "165710": {
+                    "suggested": 1,
+                    "seen": 0,
+                    "liked": 1
+                }
+            },
+            "conversationId": "391",
+            "respondentWorkerId": 1,
+            "initiatorWorkerId": 0,
+            "initiatorQuestions": {
+                "203371": {
+                    "suggested": 1,
+                    "seen": 0,
+                    "liked": 1
+                },
+                "84779": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "122159": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "151313": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "191602": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "165710": {
+                    "suggested": 1,
+                    "seen": 0,
+                    "liked": 1
+                }
+            }
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Hi there, how are you? I'm looking for movie recommendations.",
+                "system response": "I am doing okay. What kind of movies do you like?",
+                "dialog history": "",
+                "original user side information": {
+                    "user_utterance_raw": "Hi there, how are you? I'm looking for movie recommendations.",
+                    "dialog_history_raw": "",
+                    "messageId": 1021,
+                    "timeOffset": 0,
+                    "senderWorkerId": 0
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "I am doing okay. What kind of movies do you like?",
+                    "messageId": 1022,
+                    "timeOffset": 15,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 2,
+                "user utterance": "I like animations like The Triplets of Belleville (2003) and Waking Life (2001). I also enjoy Mary and Max (2009). Anything artistic.",
+                "system response": "You might like The Boss Baby (2017) that was a good movie.",
+                "dialog history": "<USER> Hi there, how are you? I'm looking for movie recommendations. <SYSTEM> I am doing okay. What kind of movies do you like?",
+                "original user side information": {
+                    "user_utterance_raw": "I like animations like @84779 and @191602. I also enjoy @122159. Anything artistic.",
+                    "dialog_history_raw": "<USER> Hi there, how are you? I'm looking for movie recommendations. <SYSTEM> I am doing okay. What kind of movies do you like?",
+                    "messageId": 1025,
+                    "timeOffset": 95,
+                    "senderWorkerId": 0
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "You might like @165710 that was a good movie.",
+                    "messageId": 1026,
+                    "timeOffset": 135,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 3,
+                "user utterance": "What's it about?",
+                "system response": "It has Alec Baldwin it is about a baby that works for a company and gets adopted it is very funny.",
+                "dialog history": "<USER> Hi there, how are you? I'm looking for movie recommendations. <SYSTEM> I am doing okay. What kind of movies do you like? <USER> I like animations like The Triplets of Belleville (2003) and Waking Life (2001). I also enjoy Mary and Max (2009). Anything artistic. <SYSTEM> You might like The Boss Baby (2017) that was a good movie.",
+                "original user side information": {
+                    "user_utterance_raw": "What's it about?",
+                    "dialog_history_raw": "<USER> Hi there, how are you? I'm looking for movie recommendations. <SYSTEM> I am doing okay. What kind of movies do you like? <USER> I like animations like @84779 and @191602. I also enjoy @122159. Anything artistic. <SYSTEM> You might like @165710 that was a good movie.",
+                    "messageId": 1027,
+                    "timeOffset": 151,
+                    "senderWorkerId": 0
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "It has Alec Baldwin it is about a baby that works for a company and gets adopted it is very funny.",
+                    "messageId": 1028,
+                    "timeOffset": 207,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 4,
+                "user utterance": "That seems like a nice comedy. Do you have any animated recommendations that are a bit more dramatic? Like A Scanner Darkly  (2006) for example. I like comedies but I prefer films with a little more depth.",
+                "system response": "That is a tough one but I will remember something. Final Fantasy: The Spirits Within (2001) was a good one.",
+                "dialog history": "<USER> Hi there, how are you? I'm looking for movie recommendations. <SYSTEM> I am doing okay. What kind of movies do you like? <USER> I like animations like The Triplets of Belleville (2003) and Waking Life (2001). I also enjoy Mary and Max (2009). Anything artistic. <SYSTEM> You might like The Boss Baby (2017) that was a good movie. <USER> What's it about? <SYSTEM> It has Alec Baldwin it is about a baby that works for a company and gets adopted it is very funny.",
+                "original user side information": {
+                    "user_utterance_raw": "That seems like a nice comedy. Do you have any animated recommendations that are a bit more dramatic? Like @151313 for example. I like comedies but I prefer films with a little more depth.",
+                    "dialog_history_raw": "<USER> Hi there, how are you? I'm looking for movie recommendations. <SYSTEM> I am doing okay. What kind of movies do you like? <USER> I like animations like @84779 and @191602. I also enjoy @122159. Anything artistic. <SYSTEM> You might like @165710 that was a good movie. <USER> What's it about? <SYSTEM> It has Alec Baldwin it is about a baby that works for a company and gets adopted it is very funny.",
+                    "messageId": 1031,
+                    "timeOffset": 327,
+                    "senderWorkerId": 0
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "That is a tough one but I will remember something. @203371 was a good one.",
+                    "messageId": 1033,
+                    "timeOffset": 509,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 5,
+                "user utterance": "Ooh that seems cool! Thanks for the input. I'm ready to submit if you are.",
+                "system response": "It is animated, sci fi, and has action. Glad I could help.",
+                "dialog history": "<USER> Hi there, how are you? I'm looking for movie recommendations. <SYSTEM> I am doing okay. What kind of movies do you like? <USER> I like animations like The Triplets of Belleville (2003) and Waking Life (2001). I also enjoy Mary and Max (2009). Anything artistic. <SYSTEM> You might like The Boss Baby (2017) that was a good movie. <USER> What's it about? <SYSTEM> It has Alec Baldwin it is about a baby that works for a company and gets adopted it is very funny. <USER> That seems like a nice comedy. Do you have any animated recommendations that are a bit more dramatic? Like A Scanner Darkly  (2006) for example. I like comedies but I prefer films with a little more depth. <SYSTEM> That is a tough one but I will remember something. Final Fantasy: The Spirits Within (2001) was a good one.",
+                "original user side information": {
+                    "user_utterance_raw": "Ooh that seems cool! Thanks for the input. I'm ready to submit if you are.",
+                    "dialog_history_raw": "<USER> Hi there, how are you? I'm looking for movie recommendations. <SYSTEM> I am doing okay. What kind of movies do you like? <USER> I like animations like @84779 and @191602. I also enjoy @122159. Anything artistic. <SYSTEM> You might like @165710 that was a good movie. <USER> What's it about? <SYSTEM> It has Alec Baldwin it is about a baby that works for a company and gets adopted it is very funny. <USER> That seems like a nice comedy. Do you have any animated recommendations that are a bit more dramatic? Like @151313 for example. I like comedies but I prefer films with a little more depth. <SYSTEM> That is a tough one but I will remember something. @203371 was a good one.",
+                    "messageId": 1034,
+                    "timeOffset": 564,
+                    "senderWorkerId": 0
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "It is animated, sci fi, and has action. Glad I could help.",
+                    "messageId": 1036,
+                    "timeOffset": 579,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 6,
+                "user utterance": "Nice. Take care, cheers!",
+                "system response": "bye.",
+                "dialog history": "<USER> Hi there, how are you? I'm looking for movie recommendations. <SYSTEM> I am doing okay. What kind of movies do you like? <USER> I like animations like The Triplets of Belleville (2003) and Waking Life (2001). I also enjoy Mary and Max (2009). Anything artistic. <SYSTEM> You might like The Boss Baby (2017) that was a good movie. <USER> What's it about? <SYSTEM> It has Alec Baldwin it is about a baby that works for a company and gets adopted it is very funny. <USER> That seems like a nice comedy. Do you have any animated recommendations that are a bit more dramatic? Like A Scanner Darkly  (2006) for example. I like comedies but I prefer films with a little more depth. <SYSTEM> That is a tough one but I will remember something. Final Fantasy: The Spirits Within (2001) was a good one. <USER> Ooh that seems cool! Thanks for the input. I'm ready to submit if you are. <SYSTEM> It is animated, sci fi, and has action. Glad I could help.",
+                "original user side information": {
+                    "user_utterance_raw": "Nice. Take care, cheers!",
+                    "dialog_history_raw": "<USER> Hi there, how are you? I'm looking for movie recommendations. <SYSTEM> I am doing okay. What kind of movies do you like? <USER> I like animations like @84779 and @191602. I also enjoy @122159. Anything artistic. <SYSTEM> You might like @165710 that was a good movie. <USER> What's it about? <SYSTEM> It has Alec Baldwin it is about a baby that works for a company and gets adopted it is very funny. <USER> That seems like a nice comedy. Do you have any animated recommendations that are a bit more dramatic? Like @151313 for example. I like comedies but I prefer films with a little more depth. <SYSTEM> That is a tough one but I will remember something. @203371 was a good one. <USER> Ooh that seems cool! Thanks for the input. I'm ready to submit if you are. <SYSTEM> It is animated, sci fi, and has action. Glad I could help.",
+                    "messageId": 1038,
+                    "timeOffset": 591,
+                    "senderWorkerId": 0
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "bye.",
+                    "messageId": 1039,
+                    "timeOffset": 608,
+                    "senderWorkerId": 1
+                }
+            }
+        ]
+    },
+    "Redial--train--2": {
+        "original dialog id": "395",
+        "dialog index": 2,
+        "original dialog info": {
+            "movieMentions": {
+                "196336": "Scarface  (1983)",
+                "204322": "South Park",
+                "145455": "Twilight Zone: The Movie (1983)",
+                "114851": "The Godfather ",
+                "128905": "From Dusk till Dawn (1996)",
+                "143189": "Star Wars: Episode II \u2013 Attack of the Clones (2002)",
+                "152242": "Enemy of the State  (1998)",
+                "204292": "Star Wars"
+            },
+            "respondentQuestions": {
+                "196336": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "204322": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "145455": {
+                    "suggested": 1,
+                    "seen": 1,
+                    "liked": 0
+                },
+                "114851": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "128905": {
+                    "suggested": 1,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "143189": {
+                    "suggested": 1,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "152242": {
+                    "suggested": 1,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "204292": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                }
+            },
+            "conversationId": "395",
+            "respondentWorkerId": 1,
+            "initiatorWorkerId": 2,
+            "initiatorQuestions": []
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Hi, did you see Scarface  (1983) ?",
+                "system response": "Yes it was a pretty good movie.",
+                "dialog history": "",
+                "original user side information": {
+                    "user_utterance_raw": "Hi, did you see @196336 ?",
+                    "dialog_history_raw": "",
+                    "messageId": 1040,
+                    "timeOffset": 0,
+                    "senderWorkerId": 2
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "Yes it was a pretty good movie.",
+                    "messageId": 1041,
+                    "timeOffset": 19,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 2,
+                "user utterance": "Then you would like The Godfather  if you haven't seen it. You like Sci Fi stuff like Star Wars ?",
+                "system response": "I am more of a Star Wars: Episode II \u2013 Attack of the Clones (2002) kind of person.",
+                "dialog history": "<USER> Hi, did you see Scarface  (1983) ? <SYSTEM> Yes it was a pretty good movie.",
+                "original user side information": {
+                    "user_utterance_raw": "Then you would like @114851 if you haven't seen it. You like Sci Fi stuff like @204292 ?",
+                    "dialog_history_raw": "<USER> Hi, did you see @196336 ? <SYSTEM> Yes it was a pretty good movie.",
+                    "messageId": 1043,
+                    "timeOffset": 102,
+                    "senderWorkerId": 2
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "I am more of a @143189 kind of person.",
+                    "messageId": 1044,
+                    "timeOffset": 113,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 3,
+                "user utterance": "Did you see any of the Star Wars parody movies? Star Wars: Episode II \u2013 Attack of the Clones (2002) was pretty funny?",
+                "system response": "I do not think I have seen that one. Who is in it?",
+                "dialog history": "<USER> Hi, did you see Scarface  (1983) ? <SYSTEM> Yes it was a pretty good movie. <USER> Then you would like The Godfather  if you haven't seen it. You like Sci Fi stuff like Star Wars ? <SYSTEM> I am more of a Star Wars: Episode II \u2013 Attack of the Clones (2002) kind of person.",
+                "original user side information": {
+                    "user_utterance_raw": "Did you see any of the Star Wars parody movies? @143189 was pretty funny?",
+                    "dialog_history_raw": "<USER> Hi, did you see @196336 ? <SYSTEM> Yes it was a pretty good movie. <USER> Then you would like @114851 if you haven't seen it. You like Sci Fi stuff like @204292 ? <SYSTEM> I am more of a @143189 kind of person.",
+                    "messageId": 1045,
+                    "timeOffset": 193,
+                    "senderWorkerId": 2
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "I do not think I have seen that one. Who is in it?",
+                    "messageId": 1046,
+                    "timeOffset": 231,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 4,
+                "user utterance": "Have you seen any cartoon movies like South Park ?",
+                "system response": "Yes those are really funny. I think I will watch Star Wars: Episode II \u2013 Attack of the Clones (2002). Thanks for the recommendation.",
+                "dialog history": "<USER> Hi, did you see Scarface  (1983) ? <SYSTEM> Yes it was a pretty good movie. <USER> Then you would like The Godfather  if you haven't seen it. You like Sci Fi stuff like Star Wars ? <SYSTEM> I am more of a Star Wars: Episode II \u2013 Attack of the Clones (2002) kind of person. <USER> Did you see any of the Star Wars parody movies? Star Wars: Episode II \u2013 Attack of the Clones (2002) was pretty funny? <SYSTEM> I do not think I have seen that one. Who is in it?",
+                "original user side information": {
+                    "user_utterance_raw": "Have you seen any cartoon movies like @204322 ?",
+                    "dialog_history_raw": "<USER> Hi, did you see @196336 ? <SYSTEM> Yes it was a pretty good movie. <USER> Then you would like @114851 if you haven't seen it. You like Sci Fi stuff like @204292 ? <SYSTEM> I am more of a @143189 kind of person. <USER> Did you see any of the Star Wars parody movies? @143189 was pretty funny? <SYSTEM> I do not think I have seen that one. Who is in it?",
+                    "messageId": 1047,
+                    "timeOffset": 243,
+                    "senderWorkerId": 2
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "Yes those are really funny. I think I will watch @143189. Thanks for the recommendation.",
+                    "messageId": 1049,
+                    "timeOffset": 290,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 5,
+                "user utterance": "Star Wars: Episode II \u2013 Attack of the Clones (2002) r Wars Clones is a claymation movie.",
+                "system response": "That sounds great.",
+                "dialog history": "<USER> Hi, did you see Scarface  (1983) ? <SYSTEM> Yes it was a pretty good movie. <USER> Then you would like The Godfather  if you haven't seen it. You like Sci Fi stuff like Star Wars ? <SYSTEM> I am more of a Star Wars: Episode II \u2013 Attack of the Clones (2002) kind of person. <USER> Did you see any of the Star Wars parody movies? Star Wars: Episode II \u2013 Attack of the Clones (2002) was pretty funny? <SYSTEM> I do not think I have seen that one. Who is in it? <USER> Have you seen any cartoon movies like South Park ? <SYSTEM> Yes those are really funny. I think I will watch Star Wars: Episode II \u2013 Attack of the Clones (2002). Thanks for the recommendation.",
+                "original user side information": {
+                    "user_utterance_raw": "@143189 r Wars Clones is a claymation movie.",
+                    "dialog_history_raw": "<USER> Hi, did you see @196336 ? <SYSTEM> Yes it was a pretty good movie. <USER> Then you would like @114851 if you haven't seen it. You like Sci Fi stuff like @204292 ? <SYSTEM> I am more of a @143189 kind of person. <USER> Did you see any of the Star Wars parody movies? @143189 was pretty funny? <SYSTEM> I do not think I have seen that one. Who is in it? <USER> Have you seen any cartoon movies like @204322 ? <SYSTEM> Yes those are really funny. I think I will watch @143189. Thanks for the recommendation.",
+                    "messageId": 1050,
+                    "timeOffset": 307,
+                    "senderWorkerId": 2
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "That sounds great.",
+                    "messageId": 1051,
+                    "timeOffset": 326,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 6,
+                "user utterance": "It is. You like blood and gore movies? If so, you might like From Dusk till Dawn (1996) .",
+                "system response": "No I do not like that genre of movie. The star wars movie is perfect for me.",
+                "dialog history": "<USER> Hi, did you see Scarface  (1983) ? <SYSTEM> Yes it was a pretty good movie. <USER> Then you would like The Godfather  if you haven't seen it. You like Sci Fi stuff like Star Wars ? <SYSTEM> I am more of a Star Wars: Episode II \u2013 Attack of the Clones (2002) kind of person. <USER> Did you see any of the Star Wars parody movies? Star Wars: Episode II \u2013 Attack of the Clones (2002) was pretty funny? <SYSTEM> I do not think I have seen that one. Who is in it? <USER> Have you seen any cartoon movies like South Park ? <SYSTEM> Yes those are really funny. I think I will watch Star Wars: Episode II \u2013 Attack of the Clones (2002). Thanks for the recommendation. <USER> Star Wars: Episode II \u2013 Attack of the Clones (2002) r Wars Clones is a claymation movie. <SYSTEM> That sounds great.",
+                "original user side information": {
+                    "user_utterance_raw": "It is. You like blood and gore movies? If so, you might like @128905 .",
+                    "dialog_history_raw": "<USER> Hi, did you see @196336 ? <SYSTEM> Yes it was a pretty good movie. <USER> Then you would like @114851 if you haven't seen it. You like Sci Fi stuff like @204292 ? <SYSTEM> I am more of a @143189 kind of person. <USER> Did you see any of the Star Wars parody movies? @143189 was pretty funny? <SYSTEM> I do not think I have seen that one. Who is in it? <USER> Have you seen any cartoon movies like @204322 ? <SYSTEM> Yes those are really funny. I think I will watch @143189. Thanks for the recommendation. <USER> @143189 r Wars Clones is a claymation movie. <SYSTEM> That sounds great.",
+                    "messageId": 1052,
+                    "timeOffset": 379,
+                    "senderWorkerId": 2
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "No I do not like that genre of movie. The star wars movie is perfect for me.",
+                    "messageId": 1053,
+                    "timeOffset": 418,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 7,
+                "user utterance": "You not a Twilight Zone: The Movie (1983) fan are you? Those films creep me out.",
+                "system response": "I found the movie I would like to watch. Thanks for all the help.",
+                "dialog history": "<USER> Hi, did you see Scarface  (1983) ? <SYSTEM> Yes it was a pretty good movie. <USER> Then you would like The Godfather  if you haven't seen it. You like Sci Fi stuff like Star Wars ? <SYSTEM> I am more of a Star Wars: Episode II \u2013 Attack of the Clones (2002) kind of person. <USER> Did you see any of the Star Wars parody movies? Star Wars: Episode II \u2013 Attack of the Clones (2002) was pretty funny? <SYSTEM> I do not think I have seen that one. Who is in it? <USER> Have you seen any cartoon movies like South Park ? <SYSTEM> Yes those are really funny. I think I will watch Star Wars: Episode II \u2013 Attack of the Clones (2002). Thanks for the recommendation. <USER> Star Wars: Episode II \u2013 Attack of the Clones (2002) r Wars Clones is a claymation movie. <SYSTEM> That sounds great. <USER> It is. You like blood and gore movies? If so, you might like From Dusk till Dawn (1996) . <SYSTEM> No I do not like that genre of movie. The star wars movie is perfect for me.",
+                "original user side information": {
+                    "user_utterance_raw": "You not a @145455 fan are you? Those films creep me out.",
+                    "dialog_history_raw": "<USER> Hi, did you see @196336 ? <SYSTEM> Yes it was a pretty good movie. <USER> Then you would like @114851 if you haven't seen it. You like Sci Fi stuff like @204292 ? <SYSTEM> I am more of a @143189 kind of person. <USER> Did you see any of the Star Wars parody movies? @143189 was pretty funny? <SYSTEM> I do not think I have seen that one. Who is in it? <USER> Have you seen any cartoon movies like @204322 ? <SYSTEM> Yes those are really funny. I think I will watch @143189. Thanks for the recommendation. <USER> @143189 r Wars Clones is a claymation movie. <SYSTEM> That sounds great. <USER> It is. You like blood and gore movies? If so, you might like @128905 . <SYSTEM> No I do not like that genre of movie. The star wars movie is perfect for me.",
+                    "messageId": 1054,
+                    "timeOffset": 462,
+                    "senderWorkerId": 2
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "I found the movie I would like to watch. Thanks for all the help.",
+                    "messageId": 1055,
+                    "timeOffset": 521,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 8,
+                "user utterance": "Oh okay. Enemy of the State  (1998) was a good tech film if you're into that genre. How do we submit?",
+                "system response": "click the hide/show movie forms and fill the movie questions rows then it will let you submit. I hope you have a great night. bye.",
+                "dialog history": "<USER> Hi, did you see Scarface  (1983) ? <SYSTEM> Yes it was a pretty good movie. <USER> Then you would like The Godfather  if you haven't seen it. You like Sci Fi stuff like Star Wars ? <SYSTEM> I am more of a Star Wars: Episode II \u2013 Attack of the Clones (2002) kind of person. <USER> Did you see any of the Star Wars parody movies? Star Wars: Episode II \u2013 Attack of the Clones (2002) was pretty funny? <SYSTEM> I do not think I have seen that one. Who is in it? <USER> Have you seen any cartoon movies like South Park ? <SYSTEM> Yes those are really funny. I think I will watch Star Wars: Episode II \u2013 Attack of the Clones (2002). Thanks for the recommendation. <USER> Star Wars: Episode II \u2013 Attack of the Clones (2002) r Wars Clones is a claymation movie. <SYSTEM> That sounds great. <USER> It is. You like blood and gore movies? If so, you might like From Dusk till Dawn (1996) . <SYSTEM> No I do not like that genre of movie. The star wars movie is perfect for me. <USER> You not a Twilight Zone: The Movie (1983) fan are you? Those films creep me out. <SYSTEM> I found the movie I would like to watch. Thanks for all the help.",
+                "original user side information": {
+                    "user_utterance_raw": "Oh okay. @152242 was a good tech film if you're into that genre. How do we submit?",
+                    "dialog_history_raw": "<USER> Hi, did you see @196336 ? <SYSTEM> Yes it was a pretty good movie. <USER> Then you would like @114851 if you haven't seen it. You like Sci Fi stuff like @204292 ? <SYSTEM> I am more of a @143189 kind of person. <USER> Did you see any of the Star Wars parody movies? @143189 was pretty funny? <SYSTEM> I do not think I have seen that one. Who is in it? <USER> Have you seen any cartoon movies like @204322 ? <SYSTEM> Yes those are really funny. I think I will watch @143189. Thanks for the recommendation. <USER> @143189 r Wars Clones is a claymation movie. <SYSTEM> That sounds great. <USER> It is. You like blood and gore movies? If so, you might like @128905 . <SYSTEM> No I do not like that genre of movie. The star wars movie is perfect for me. <USER> You not a @145455 fan are you? Those films creep me out. <SYSTEM> I found the movie I would like to watch. Thanks for all the help.",
+                    "messageId": 1057,
+                    "timeOffset": 570,
+                    "senderWorkerId": 2
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "click the hide/show movie forms and fill the movie questions rows then it will let you submit. I hope you have a great night. bye.",
+                    "messageId": 1059,
+                    "timeOffset": 623,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 9,
+                "user utterance": "Thanks.",
+                "system response": "",
+                "dialog history": "<USER> Hi, did you see Scarface  (1983) ? <SYSTEM> Yes it was a pretty good movie. <USER> Then you would like The Godfather  if you haven't seen it. You like Sci Fi stuff like Star Wars ? <SYSTEM> I am more of a Star Wars: Episode II \u2013 Attack of the Clones (2002) kind of person. <USER> Did you see any of the Star Wars parody movies? Star Wars: Episode II \u2013 Attack of the Clones (2002) was pretty funny? <SYSTEM> I do not think I have seen that one. Who is in it? <USER> Have you seen any cartoon movies like South Park ? <SYSTEM> Yes those are really funny. I think I will watch Star Wars: Episode II \u2013 Attack of the Clones (2002). Thanks for the recommendation. <USER> Star Wars: Episode II \u2013 Attack of the Clones (2002) r Wars Clones is a claymation movie. <SYSTEM> That sounds great. <USER> It is. You like blood and gore movies? If so, you might like From Dusk till Dawn (1996) . <SYSTEM> No I do not like that genre of movie. The star wars movie is perfect for me. <USER> You not a Twilight Zone: The Movie (1983) fan are you? Those films creep me out. <SYSTEM> I found the movie I would like to watch. Thanks for all the help. <USER> Oh okay. Enemy of the State  (1998) was a good tech film if you're into that genre. How do we submit? <SYSTEM> click the hide/show movie forms and fill the movie questions rows then it will let you submit. I hope you have a great night. bye.",
+                "original user side information": {
+                    "user_utterance_raw": "Thanks.",
+                    "dialog_history_raw": "<USER> Hi, did you see @196336 ? <SYSTEM> Yes it was a pretty good movie. <USER> Then you would like @114851 if you haven't seen it. You like Sci Fi stuff like @204292 ? <SYSTEM> I am more of a @143189 kind of person. <USER> Did you see any of the Star Wars parody movies? @143189 was pretty funny? <SYSTEM> I do not think I have seen that one. Who is in it? <USER> Have you seen any cartoon movies like @204322 ? <SYSTEM> Yes those are really funny. I think I will watch @143189. Thanks for the recommendation. <USER> @143189 r Wars Clones is a claymation movie. <SYSTEM> That sounds great. <USER> It is. You like blood and gore movies? If so, you might like @128905 . <SYSTEM> No I do not like that genre of movie. The star wars movie is perfect for me. <USER> You not a @145455 fan are you? Those films creep me out. <SYSTEM> I found the movie I would like to watch. Thanks for all the help. <USER> Oh okay. @152242 was a good tech film if you're into that genre. How do we submit? <SYSTEM> click the hide/show movie forms and fill the movie questions rows then it will let you submit. I hope you have a great night. bye.",
+                    "messageId": 1060,
+                    "timeOffset": 628,
+                    "senderWorkerId": 2
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "",
+                    "messageId": 1059,
+                    "timeOffset": 623,
+                    "senderWorkerId": 1
+                }
+            }
+        ]
+    },
+    "Redial--train--3": {
+        "original dialog id": "397",
+        "dialog index": 3,
+        "original dialog info": {
+            "movieMentions": {
+                "79320": "Contact  (2009)",
+                "84001": "Donnie Darko (2001)",
+                "155969": "The Martian  (2015)",
+                "90950": "Avatar  (2009)",
+                "163606": "Avatar ",
+                "147598": "Indiana Jones and the Kingdom of the Crystal Skull (2008)",
+                "204292": "Star Wars"
+            },
+            "respondentQuestions": {
+                "79320": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "84001": {
+                    "suggested": 1,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "155969": {
+                    "suggested": 1,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "90950": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "163606": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "147598": {
+                    "suggested": 0,
+                    "seen": 0,
+                    "liked": 1
+                },
+                "204292": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                }
+            },
+            "conversationId": "397",
+            "respondentWorkerId": 1,
+            "initiatorWorkerId": 3,
+            "initiatorQuestions": {
+                "79320": {
+                    "suggested": 0,
+                    "seen": 0,
+                    "liked": 1
+                },
+                "84001": {
+                    "suggested": 0,
+                    "seen": 0,
+                    "liked": 1
+                },
+                "155969": {
+                    "suggested": 0,
+                    "seen": 0,
+                    "liked": 1
+                },
+                "90950": {
+                    "suggested": 0,
+                    "seen": 0,
+                    "liked": 1
+                },
+                "163606": {
+                    "suggested": 0,
+                    "seen": 0,
+                    "liked": 0
+                },
+                "147598": {
+                    "suggested": 1,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "204292": {
+                    "suggested": 1,
+                    "seen": 1,
+                    "liked": 1
+                }
+            }
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Avatar  It is a nice movie. What say? Avatar  (2009) Was a marvelous 3D experience personally for me.",
+                "system response": "I really liked that movie but haven't seen it in a while. Are you a Michelle Rodriquez fan?",
+                "dialog history": "",
+                "original user side information": {
+                    "user_utterance_raw": "@163606 It is a nice movie. What say? @90950 Was a marvelous 3D experience personally for me.",
+                    "dialog_history_raw": "",
+                    "messageId": 1062,
+                    "timeOffset": 31,
+                    "senderWorkerId": 3
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "I really liked that movie but haven't seen it in a while. Are you a Michelle Rodriquez fan?",
+                    "messageId": 1063,
+                    "timeOffset": 56,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 2,
+                "user utterance": "No. I am not. I like sci-fi movies. Have you watched The Martian  (2015). My another favorite sci-fi movies are Contact  (2009) and Donnie Darko (2001).",
+                "system response": "No I have not seen that one but have seen all the Star Wars movies. Do you like those.",
+                "dialog history": "<USER> Avatar  It is a nice movie. What say? Avatar  (2009) Was a marvelous 3D experience personally for me. <SYSTEM> I really liked that movie but haven't seen it in a while. Are you a Michelle Rodriquez fan?",
+                "original user side information": {
+                    "user_utterance_raw": "No. I am not. I like sci-fi movies. Have you watched @155969. My another favorite sci-fi movies are @79320 and @84001.",
+                    "dialog_history_raw": "<USER> @163606 It is a nice movie. What say? @90950 Was a marvelous 3D experience personally for me. <SYSTEM> I really liked that movie but haven't seen it in a while. Are you a Michelle Rodriquez fan?",
+                    "messageId": 1065,
+                    "timeOffset": 146,
+                    "senderWorkerId": 3
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "No I have not seen that one but have seen all the @204292 movies. Do you like those.",
+                    "messageId": 1066,
+                    "timeOffset": 159,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 3,
+                "user utterance": "Yes, I love Star Wars series. In fact I am excited about the upcoming Star Wars. What are you favorite movies?",
+                "system response": "I am too I think you will like Indiana Jones and the Kingdom of the Crystal Skull (2008).",
+                "dialog history": "<USER> Avatar  It is a nice movie. What say? Avatar  (2009) Was a marvelous 3D experience personally for me. <SYSTEM> I really liked that movie but haven't seen it in a while. Are you a Michelle Rodriquez fan? <USER> No. I am not. I like sci-fi movies. Have you watched The Martian  (2015). My another favorite sci-fi movies are Contact  (2009) and Donnie Darko (2001). <SYSTEM> No I have not seen that one but have seen all the Star Wars movies. Do you like those.",
+                "original user side information": {
+                    "user_utterance_raw": "Yes, I love @204292 series. In fact I am excited about the upcoming @204292. What are you favorite movies?",
+                    "dialog_history_raw": "<USER> @163606 It is a nice movie. What say? @90950 Was a marvelous 3D experience personally for me. <SYSTEM> I really liked that movie but haven't seen it in a while. Are you a Michelle Rodriquez fan? <USER> No. I am not. I like sci-fi movies. Have you watched @155969. My another favorite sci-fi movies are @79320 and @84001. <SYSTEM> No I have not seen that one but have seen all the @204292 movies. Do you like those.",
+                    "messageId": 1069,
+                    "timeOffset": 231,
+                    "senderWorkerId": 3
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "I am too I think you will like @147598.",
+                    "messageId": 1070,
+                    "timeOffset": 249,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 4,
+                "user utterance": "I have not seen Indiana Jones and the Kingdom of the Crystal Skull (2008). I will watch it soon.",
+                "system response": "It is a good movie if you like Star wars you should like it.",
+                "dialog history": "<USER> Avatar  It is a nice movie. What say? Avatar  (2009) Was a marvelous 3D experience personally for me. <SYSTEM> I really liked that movie but haven't seen it in a while. Are you a Michelle Rodriquez fan? <USER> No. I am not. I like sci-fi movies. Have you watched The Martian  (2015). My another favorite sci-fi movies are Contact  (2009) and Donnie Darko (2001). <SYSTEM> No I have not seen that one but have seen all the Star Wars movies. Do you like those. <USER> Yes, I love Star Wars series. In fact I am excited about the upcoming Star Wars. What are you favorite movies? <SYSTEM> I am too I think you will like Indiana Jones and the Kingdom of the Crystal Skull (2008).",
+                "original user side information": {
+                    "user_utterance_raw": "I have not seen @147598. I will watch it soon.",
+                    "dialog_history_raw": "<USER> @163606 It is a nice movie. What say? @90950 Was a marvelous 3D experience personally for me. <SYSTEM> I really liked that movie but haven't seen it in a while. Are you a Michelle Rodriquez fan? <USER> No. I am not. I like sci-fi movies. Have you watched @155969. My another favorite sci-fi movies are @79320 and @84001. <SYSTEM> No I have not seen that one but have seen all the @204292 movies. Do you like those. <USER> Yes, I love @204292 series. In fact I am excited about the upcoming @204292. What are you favorite movies? <SYSTEM> I am too I think you will like @147598.",
+                    "messageId": 1072,
+                    "timeOffset": 283,
+                    "senderWorkerId": 3
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "It is a good movie if you like Star wars you should like it.",
+                    "messageId": 1073,
+                    "timeOffset": 312,
+                    "senderWorkerId": 1
+                }
+            },
+            {
+                "turn id": 5,
+                "user utterance": "Great. I will watch those. Now, let us submit this. Nice talking to you, have a nice day!",
+                "system response": "Thanks it was nice talking to you too bye.",
+                "dialog history": "<USER> Avatar  It is a nice movie. What say? Avatar  (2009) Was a marvelous 3D experience personally for me. <SYSTEM> I really liked that movie but haven't seen it in a while. Are you a Michelle Rodriquez fan? <USER> No. I am not. I like sci-fi movies. Have you watched The Martian  (2015). My another favorite sci-fi movies are Contact  (2009) and Donnie Darko (2001). <SYSTEM> No I have not seen that one but have seen all the Star Wars movies. Do you like those. <USER> Yes, I love Star Wars series. In fact I am excited about the upcoming Star Wars. What are you favorite movies? <SYSTEM> I am too I think you will like Indiana Jones and the Kingdom of the Crystal Skull (2008). <USER> I have not seen Indiana Jones and the Kingdom of the Crystal Skull (2008). I will watch it soon. <SYSTEM> It is a good movie if you like Star wars you should like it.",
+                "original user side information": {
+                    "user_utterance_raw": "Great. I will watch those. Now, let us submit this. Nice talking to you, have a nice day!",
+                    "dialog_history_raw": "<USER> @163606 It is a nice movie. What say? @90950 Was a marvelous 3D experience personally for me. <SYSTEM> I really liked that movie but haven't seen it in a while. Are you a Michelle Rodriquez fan? <USER> No. I am not. I like sci-fi movies. Have you watched @155969. My another favorite sci-fi movies are @79320 and @84001. <SYSTEM> No I have not seen that one but have seen all the @204292 movies. Do you like those. <USER> Yes, I love @204292 series. In fact I am excited about the upcoming @204292. What are you favorite movies? <SYSTEM> I am too I think you will like @147598. <USER> I have not seen @147598. I will watch it soon. <SYSTEM> It is a good movie if you like Star wars you should like it.",
+                    "messageId": 1074,
+                    "timeOffset": 344,
+                    "senderWorkerId": 3
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "Thanks it was nice talking to you too bye.",
+                    "messageId": 1075,
+                    "timeOffset": 361,
+                    "senderWorkerId": 1
+                }
+            }
+        ]
+    },
+    "Redial--train--4": {
+        "original dialog id": "405",
+        "dialog index": 4,
+        "original dialog info": {
+            "movieMentions": {
+                "188302": "Ever After (1998)",
+                "195904": "Charlie's Angels ",
+                "91313": "Blended  (2014)",
+                "157394": "The Wedding Singer (1998)",
+                "115908": "50 First Dates (2004)"
+            },
+            "respondentQuestions": [],
+            "conversationId": "405",
+            "respondentWorkerId": 5,
+            "initiatorWorkerId": 4,
+            "initiatorQuestions": []
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "I'm in the mood to watch a romantic comedy.  What do you suggest?",
+                "system response": "50 First Dates (2004). Have you seen that one?",
+                "dialog history": "",
+                "original user side information": {
+                    "user_utterance_raw": "I'm in the mood to watch a romantic comedy.  What do you suggest?",
+                    "dialog_history_raw": "",
+                    "messageId": 1076,
+                    "timeOffset": 0,
+                    "senderWorkerId": 4
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "@115908. Have you seen that one?",
+                    "messageId": 1078,
+                    "timeOffset": 36,
+                    "senderWorkerId": 5
+                }
+            },
+            {
+                "turn id": 2,
+                "user utterance": "Oh, I've seen that one.  I really like Drew Barrymore.",
+                "system response": "Yes she is good, I am looking for a super hero movie myself. Do you like The Wedding Singer (1998).",
+                "dialog history": "<USER> I'm in the mood to watch a romantic comedy.  What do you suggest? <SYSTEM> 50 First Dates (2004). Have you seen that one?",
+                "original user side information": {
+                    "user_utterance_raw": "Oh, I've seen that one.  I really like Drew Barrymore.",
+                    "dialog_history_raw": "<USER> I'm in the mood to watch a romantic comedy.  What do you suggest? <SYSTEM> @115908. Have you seen that one?",
+                    "messageId": 1079,
+                    "timeOffset": 91,
+                    "senderWorkerId": 4
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "Yes she is good, I am looking for a super hero movie myself. Do you like @157394.",
+                    "messageId": 1081,
+                    "timeOffset": 169,
+                    "senderWorkerId": 5
+                }
+            },
+            {
+                "turn id": 3,
+                "user utterance": "Drew Barrymore was in Charlie's Angels .  Do you think that counts as a superhero movie?",
+                "system response": "Yeah, definitely. I liked that one.",
+                "dialog history": "<USER> I'm in the mood to watch a romantic comedy.  What do you suggest? <SYSTEM> 50 First Dates (2004). Have you seen that one? <USER> Oh, I've seen that one.  I really like Drew Barrymore. <SYSTEM> Yes she is good, I am looking for a super hero movie myself. Do you like The Wedding Singer (1998).",
+                "original user side information": {
+                    "user_utterance_raw": "Drew Barrymore was in @195904.  Do you think that counts as a superhero movie?",
+                    "dialog_history_raw": "<USER> I'm in the mood to watch a romantic comedy.  What do you suggest? <SYSTEM> @115908. Have you seen that one? <USER> Oh, I've seen that one.  I really like Drew Barrymore. <SYSTEM> Yes she is good, I am looking for a super hero movie myself. Do you like @157394.",
+                    "messageId": 1082,
+                    "timeOffset": 188,
+                    "senderWorkerId": 4
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "Yeah, definitely. I liked that one.",
+                    "messageId": 1083,
+                    "timeOffset": 199,
+                    "senderWorkerId": 5
+                }
+            },
+            {
+                "turn id": 4,
+                "user utterance": "Oh, The Wedding Singer (1998) is a good one.  Sandler and Barrymore are great together.  I'm very excited to finally see Blended  (2014).",
+                "system response": "Oh I have heard good things about that film.",
+                "dialog history": "<USER> I'm in the mood to watch a romantic comedy.  What do you suggest? <SYSTEM> 50 First Dates (2004). Have you seen that one? <USER> Oh, I've seen that one.  I really like Drew Barrymore. <SYSTEM> Yes she is good, I am looking for a super hero movie myself. Do you like The Wedding Singer (1998). <USER> Drew Barrymore was in Charlie's Angels .  Do you think that counts as a superhero movie? <SYSTEM> Yeah, definitely. I liked that one.",
+                "original user side information": {
+                    "user_utterance_raw": "Oh, @157394 is a good one.  Sandler and Barrymore are great together.  I'm very excited to finally see @91313.",
+                    "dialog_history_raw": "<USER> I'm in the mood to watch a romantic comedy.  What do you suggest? <SYSTEM> @115908. Have you seen that one? <USER> Oh, I've seen that one.  I really like Drew Barrymore. <SYSTEM> Yes she is good, I am looking for a super hero movie myself. Do you like @157394. <USER> Drew Barrymore was in @195904.  Do you think that counts as a superhero movie? <SYSTEM> Yeah, definitely. I liked that one.",
+                    "messageId": 1084,
+                    "timeOffset": 300,
+                    "senderWorkerId": 4
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "Oh I have heard good things about that film.",
+                    "messageId": 1085,
+                    "timeOffset": 320,
+                    "senderWorkerId": 5
+                }
+            },
+            {
+                "turn id": 5,
+                "user utterance": "I also liked Barrymore in Ever After (1998).",
+                "system response": "That is one film I should definitely check out.",
+                "dialog history": "<USER> I'm in the mood to watch a romantic comedy.  What do you suggest? <SYSTEM> 50 First Dates (2004). Have you seen that one? <USER> Oh, I've seen that one.  I really like Drew Barrymore. <SYSTEM> Yes she is good, I am looking for a super hero movie myself. Do you like The Wedding Singer (1998). <USER> Drew Barrymore was in Charlie's Angels .  Do you think that counts as a superhero movie? <SYSTEM> Yeah, definitely. I liked that one. <USER> Oh, The Wedding Singer (1998) is a good one.  Sandler and Barrymore are great together.  I'm very excited to finally see Blended  (2014). <SYSTEM> Oh I have heard good things about that film.",
+                "original user side information": {
+                    "user_utterance_raw": "I also liked Barrymore in @188302.",
+                    "dialog_history_raw": "<USER> I'm in the mood to watch a romantic comedy.  What do you suggest? <SYSTEM> @115908. Have you seen that one? <USER> Oh, I've seen that one.  I really like Drew Barrymore. <SYSTEM> Yes she is good, I am looking for a super hero movie myself. Do you like @157394. <USER> Drew Barrymore was in @195904.  Do you think that counts as a superhero movie? <SYSTEM> Yeah, definitely. I liked that one. <USER> Oh, @157394 is a good one.  Sandler and Barrymore are great together.  I'm very excited to finally see @91313. <SYSTEM> Oh I have heard good things about that film.",
+                    "messageId": 1086,
+                    "timeOffset": 358,
+                    "senderWorkerId": 4
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "That is one film I should definitely check out.",
+                    "messageId": 1090,
+                    "timeOffset": 458,
+                    "senderWorkerId": 5
+                }
+            }
+        ]
+    },
+    "Redial--train--5": {
+        "original dialog id": "407",
+        "dialog index": 5,
+        "original dialog info": {
+            "movieMentions": {
+                "119144": "Wonder Woman  (2017)",
+                "125431": "Annabelle  (2014)",
+                "141788": "Fast & Furious  (2009)",
+                "204331": "Girls Trip (2017)",
+                "184418": "Get Out (2017)",
+                "136632": "Spider-Man: Homecoming (2017)"
+            },
+            "respondentQuestions": {
+                "119144": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "125431": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "141788": {
+                    "suggested": 1,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "204331": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "184418": {
+                    "suggested": 1,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "136632": {
+                    "suggested": 0,
+                    "seen": 0,
+                    "liked": 1
+                }
+            },
+            "conversationId": "407",
+            "respondentWorkerId": 6,
+            "initiatorWorkerId": 7,
+            "initiatorQuestions": {
+                "119144": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "125431": {
+                    "suggested": 1,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "141788": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "204331": {
+                    "suggested": 1,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "184418": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                },
+                "136632": {
+                    "suggested": 0,
+                    "seen": 1,
+                    "liked": 1
+                }
+            }
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "",
+                "system response": "Hello.",
+                "dialog history": "",
+                "original user side information": {
+                    "user_utterance_raw": "",
+                    "dialog_history_raw": "",
+                    "messageId": 1086,
+                    "timeOffset": 358,
+                    "senderWorkerId": 4
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "Hello.",
+                    "messageId": 1087,
+                    "timeOffset": 0,
+                    "senderWorkerId": 6
+                }
+            },
+            {
+                "turn id": 2,
+                "user utterance": "Hello. What movie would you suggest to watch.",
+                "system response": "Get Out (2017). Have you seen that movie before?",
+                "dialog history": "<SYSTEM> Hello.",
+                "original user side information": {
+                    "user_utterance_raw": "Hello. What movie would you suggest to watch.",
+                    "dialog_history_raw": "<SYSTEM> Hello.",
+                    "messageId": 1089,
+                    "timeOffset": 51,
+                    "senderWorkerId": 7
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "@184418. Have you seen that movie before?",
+                    "messageId": 1092,
+                    "timeOffset": 171,
+                    "senderWorkerId": 6
+                }
+            },
+            {
+                "turn id": 3,
+                "user utterance": "I love that scary movies. I love Annabelle  (2014).",
+                "system response": "Yes I love Annabelle as well. That is a good movie.",
+                "dialog history": "<SYSTEM> Hello. <USER> Hello. What movie would you suggest to watch. <SYSTEM> Get Out (2017). Have you seen that movie before?",
+                "original user side information": {
+                    "user_utterance_raw": "I love that scary movies. I love @125431.",
+                    "dialog_history_raw": "<SYSTEM> Hello. <USER> Hello. What movie would you suggest to watch. <SYSTEM> @184418. Have you seen that movie before?",
+                    "messageId": 1093,
+                    "timeOffset": 171,
+                    "senderWorkerId": 7
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "Yes I love Annabelle as well. That is a good movie.",
+                    "messageId": 1095,
+                    "timeOffset": 197,
+                    "senderWorkerId": 6
+                }
+            },
+            {
+                "turn id": 4,
+                "user utterance": "I never knew a doll could be so scary.",
+                "system response": "Me either. But I love scary movies. What other movies do you like to watch?",
+                "dialog history": "<SYSTEM> Hello. <USER> Hello. What movie would you suggest to watch. <SYSTEM> Get Out (2017). Have you seen that movie before? <USER> I love that scary movies. I love Annabelle  (2014). <SYSTEM> Yes I love Annabelle as well. That is a good movie.",
+                "original user side information": {
+                    "user_utterance_raw": "I never knew a doll could be so scary.",
+                    "dialog_history_raw": "<SYSTEM> Hello. <USER> Hello. What movie would you suggest to watch. <SYSTEM> @184418. Have you seen that movie before? <USER> I love that scary movies. I love @125431. <SYSTEM> Yes I love Annabelle as well. That is a good movie.",
+                    "messageId": 1096,
+                    "timeOffset": 206,
+                    "senderWorkerId": 7
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "Me either. But I love scary movies. What other movies do you like to watch?",
+                    "messageId": 1098,
+                    "timeOffset": 237,
+                    "senderWorkerId": 6
+                }
+            },
+            {
+                "turn id": 5,
+                "user utterance": "Funny movies! LIke Girls Trip (2017). What about you.",
+                "system response": "Yes I love that movie. I never get tired of watching it. I like certain action movies li-03i25. I like certain action movies like Fast & Furious  (2009).",
+                "dialog history": "<SYSTEM> Hello. <USER> Hello. What movie would you suggest to watch. <SYSTEM> Get Out (2017). Have you seen that movie before? <USER> I love that scary movies. I love Annabelle  (2014). <SYSTEM> Yes I love Annabelle as well. That is a good movie. <USER> I never knew a doll could be so scary. <SYSTEM> Me either. But I love scary movies. What other movies do you like to watch?",
+                "original user side information": {
+                    "user_utterance_raw": "Funny movies! LIke @204331. What about you.",
+                    "dialog_history_raw": "<SYSTEM> Hello. <USER> Hello. What movie would you suggest to watch. <SYSTEM> @184418. Have you seen that movie before? <USER> I love that scary movies. I love @125431. <SYSTEM> Yes I love Annabelle as well. That is a good movie. <USER> I never knew a doll could be so scary. <SYSTEM> Me either. But I love scary movies. What other movies do you like to watch?",
+                    "messageId": 1100,
+                    "timeOffset": 319,
+                    "senderWorkerId": 7
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "Yes I love that movie. I never get tired of watching it. I like certain action movies li-03i25. I like certain action movies like @141788.",
+                    "messageId": 1103,
+                    "timeOffset": 379,
+                    "senderWorkerId": 6
+                }
+            },
+            {
+                "turn id": 6,
+                "user utterance": "Me too! I love all those movies. I also like Wonder Woman  (2017).",
+                "system response": "Yes Wonder Woman  (2017) is a good movie too.",
+                "dialog history": "<SYSTEM> Hello. <USER> Hello. What movie would you suggest to watch. <SYSTEM> Get Out (2017). Have you seen that movie before? <USER> I love that scary movies. I love Annabelle  (2014). <SYSTEM> Yes I love Annabelle as well. That is a good movie. <USER> I never knew a doll could be so scary. <SYSTEM> Me either. But I love scary movies. What other movies do you like to watch? <USER> Funny movies! LIke Girls Trip (2017). What about you. <SYSTEM> Yes I love that movie. I never get tired of watching it. I like certain action movies li-03i25. I like certain action movies like Fast & Furious  (2009).",
+                "original user side information": {
+                    "user_utterance_raw": "Me too! I love all those movies. I also like @119144.",
+                    "dialog_history_raw": "<SYSTEM> Hello. <USER> Hello. What movie would you suggest to watch. <SYSTEM> @184418. Have you seen that movie before? <USER> I love that scary movies. I love @125431. <SYSTEM> Yes I love Annabelle as well. That is a good movie. <USER> I never knew a doll could be so scary. <SYSTEM> Me either. But I love scary movies. What other movies do you like to watch? <USER> Funny movies! LIke @204331. What about you. <SYSTEM> Yes I love that movie. I never get tired of watching it. I like certain action movies li-03i25. I like certain action movies like @141788.",
+                    "messageId": 1104,
+                    "timeOffset": 419,
+                    "senderWorkerId": 7
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "Yes @119144 is a good movie too.",
+                    "messageId": 1105,
+                    "timeOffset": 447,
+                    "senderWorkerId": 6
+                }
+            },
+            {
+                "turn id": 7,
+                "user utterance": "And also Spider-Man: Homecoming (2017).",
+                "system response": "I haven't seen that movie yet.",
+                "dialog history": "<SYSTEM> Hello. <USER> Hello. What movie would you suggest to watch. <SYSTEM> Get Out (2017). Have you seen that movie before? <USER> I love that scary movies. I love Annabelle  (2014). <SYSTEM> Yes I love Annabelle as well. That is a good movie. <USER> I never knew a doll could be so scary. <SYSTEM> Me either. But I love scary movies. What other movies do you like to watch? <USER> Funny movies! LIke Girls Trip (2017). What about you. <SYSTEM> Yes I love that movie. I never get tired of watching it. I like certain action movies li-03i25. I like certain action movies like Fast & Furious  (2009). <USER> Me too! I love all those movies. I also like Wonder Woman  (2017). <SYSTEM> Yes Wonder Woman  (2017) is a good movie too.",
+                "original user side information": {
+                    "user_utterance_raw": "And also @136632.",
+                    "dialog_history_raw": "<SYSTEM> Hello. <USER> Hello. What movie would you suggest to watch. <SYSTEM> @184418. Have you seen that movie before? <USER> I love that scary movies. I love @125431. <SYSTEM> Yes I love Annabelle as well. That is a good movie. <USER> I never knew a doll could be so scary. <SYSTEM> Me either. But I love scary movies. What other movies do you like to watch? <USER> Funny movies! LIke @204331. What about you. <SYSTEM> Yes I love that movie. I never get tired of watching it. I like certain action movies li-03i25. I like certain action movies like @141788. <USER> Me too! I love all those movies. I also like @119144. <SYSTEM> Yes @119144 is a good movie too.",
+                    "messageId": 1106,
+                    "timeOffset": 486,
+                    "senderWorkerId": 7
+                },
+                "original system side information": {
+                    "sys_utterance_raw": "I haven't seen that movie yet.",
+                    "messageId": 1107,
+                    "timeOffset": 498,
+                    "senderWorkerId": 6
+                }
+            }
+        ]
+    }
+}

conversational-recommendation-dialogues/Redial/original_examples.json

@@ -0,0 +1,848 @@
+[
+    {
+        "movieMentions": {
+            "203371": "Final Fantasy: The Spirits Within (2001)",
+            "84779": "The Triplets of Belleville (2003)",
+            "122159": "Mary and Max (2009)",
+            "151313": "A Scanner Darkly  (2006)",
+            "191602": "Waking Life (2001)",
+            "165710": "The Boss Baby (2017)"
+        },
+        "respondentQuestions": {
+            "203371": {
+                "suggested": 1,
+                "seen": 0,
+                "liked": 1
+            },
+            "84779": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "122159": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "151313": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "191602": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "165710": {
+                "suggested": 1,
+                "seen": 0,
+                "liked": 1
+            }
+        },
+        "messages": [
+            {
+                "timeOffset": 0,
+                "text": "Hi there, how are you? I'm looking for movie recommendations.",
+                "senderWorkerId": 0,
+                "messageId": 1021
+            },
+            {
+                "timeOffset": 15,
+                "text": "I am doing okay. What kind of movies do you like?",
+                "senderWorkerId": 1,
+                "messageId": 1022
+            },
+            {
+                "timeOffset": 66,
+                "text": "I like animations like @84779 and @191602.",
+                "senderWorkerId": 0,
+                "messageId": 1023
+            },
+            {
+                "timeOffset": 86,
+                "text": "I also enjoy @122159.",
+                "senderWorkerId": 0,
+                "messageId": 1024
+            },
+            {
+                "timeOffset": 95,
+                "text": "Anything artistic.",
+                "senderWorkerId": 0,
+                "messageId": 1025
+            },
+            {
+                "timeOffset": 135,
+                "text": "You might like @165710 that was a good movie.",
+                "senderWorkerId": 1,
+                "messageId": 1026
+            },
+            {
+                "timeOffset": 151,
+                "text": "What's it about?",
+                "senderWorkerId": 0,
+                "messageId": 1027
+            },
+            {
+                "timeOffset": 207,
+                "text": "It has Alec Baldwin it is about a baby that works for a company and gets adopted it is very funny.",
+                "senderWorkerId": 1,
+                "messageId": 1028
+            },
+            {
+                "timeOffset": 238,
+                "text": "That seems like a nice comedy.",
+                "senderWorkerId": 0,
+                "messageId": 1029
+            },
+            {
+                "timeOffset": 272,
+                "text": "Do you have any animated recommendations that are a bit more dramatic? Like @151313 for example.",
+                "senderWorkerId": 0,
+                "messageId": 1030
+            },
+            {
+                "timeOffset": 327,
+                "text": "I like comedies but I prefer films with a little more depth.",
+                "senderWorkerId": 0,
+                "messageId": 1031
+            },
+            {
+                "timeOffset": 467,
+                "text": "That is a tough one but I will remember something.",
+                "senderWorkerId": 1,
+                "messageId": 1032
+            },
+            {
+                "timeOffset": 509,
+                "text": "@203371 was a good one.",
+                "senderWorkerId": 1,
+                "messageId": 1033
+            },
+            {
+                "timeOffset": 564,
+                "text": "Ooh that seems cool! Thanks for the input. I'm ready to submit if you are.",
+                "senderWorkerId": 0,
+                "messageId": 1034
+            },
+            {
+                "timeOffset": 571,
+                "text": "It is animated, sci fi, and has action.",
+                "senderWorkerId": 1,
+                "messageId": 1035
+            },
+            {
+                "timeOffset": 579,
+                "text": "Glad I could help.",
+                "senderWorkerId": 1,
+                "messageId": 1036
+            },
+            {
+                "timeOffset": 581,
+                "text": "Nice.",
+                "senderWorkerId": 0,
+                "messageId": 1037
+            },
+            {
+                "timeOffset": 591,
+                "text": "Take care, cheers!",
+                "senderWorkerId": 0,
+                "messageId": 1038
+            },
+            {
+                "timeOffset": 608,
+                "text": "bye.",
+                "senderWorkerId": 1,
+                "messageId": 1039
+            }
+        ],
+        "conversationId": "391",
+        "respondentWorkerId": 1,
+        "initiatorWorkerId": 0,
+        "initiatorQuestions": {
+            "203371": {
+                "suggested": 1,
+                "seen": 0,
+                "liked": 1
+            },
+            "84779": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "122159": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "151313": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "191602": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "165710": {
+                "suggested": 1,
+                "seen": 0,
+                "liked": 1
+            }
+        }
+    },
+    {
+        "movieMentions": {
+            "196336": "Scarface  (1983)",
+            "204322": "South Park",
+            "145455": "Twilight Zone: The Movie (1983)",
+            "114851": "The Godfather ",
+            "128905": "From Dusk till Dawn (1996)",
+            "143189": "Star Wars: Episode II \u2013 Attack of the Clones (2002)",
+            "152242": "Enemy of the State  (1998)",
+            "204292": "Star Wars"
+        },
+        "respondentQuestions": {
+            "196336": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "204322": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "145455": {
+                "suggested": 1,
+                "seen": 1,
+                "liked": 0
+            },
+            "114851": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "128905": {
+                "suggested": 1,
+                "seen": 1,
+                "liked": 1
+            },
+            "143189": {
+                "suggested": 1,
+                "seen": 1,
+                "liked": 1
+            },
+            "152242": {
+                "suggested": 1,
+                "seen": 1,
+                "liked": 1
+            },
+            "204292": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            }
+        },
+        "messages": [
+            {
+                "timeOffset": 0,
+                "text": "Hi, did you see @196336 ?",
+                "senderWorkerId": 2,
+                "messageId": 1040
+            },
+            {
+                "timeOffset": 19,
+                "text": "Yes it was a pretty good movie.",
+                "senderWorkerId": 1,
+                "messageId": 1041
+            },
+            {
+                "timeOffset": 69,
+                "text": "Then you would like @114851 if you haven't seen it.",
+                "senderWorkerId": 2,
+                "messageId": 1042
+            },
+            {
+                "timeOffset": 102,
+                "text": "You like Sci Fi stuff like @204292 ?",
+                "senderWorkerId": 2,
+                "messageId": 1043
+            },
+            {
+                "timeOffset": 113,
+                "text": "I am more of a @143189 kind of person.",
+                "senderWorkerId": 1,
+                "messageId": 1044
+            },
+            {
+                "timeOffset": 193,
+                "text": "Did you see any of the Star Wars parody movies? @143189 was pretty funny?",
+                "senderWorkerId": 2,
+                "messageId": 1045
+            },
+            {
+                "timeOffset": 231,
+                "text": "I do not think I have seen that one. Who is in it?",
+                "senderWorkerId": 1,
+                "messageId": 1046
+            },
+            {
+                "timeOffset": 243,
+                "text": "Have you seen any cartoon movies like @204322 ?",
+                "senderWorkerId": 2,
+                "messageId": 1047
+            },
+            {
+                "timeOffset": 278,
+                "text": "Yes those are really funny. I think I will watch @143189.",
+                "senderWorkerId": 1,
+                "messageId": 1048
+            },
+            {
+                "timeOffset": 290,
+                "text": "Thanks for the recommendation.",
+                "senderWorkerId": 1,
+                "messageId": 1049
+            },
+            {
+                "timeOffset": 307,
+                "text": "@143189 r Wars Clones is a claymation movie.",
+                "senderWorkerId": 2,
+                "messageId": 1050
+            },
+            {
+                "timeOffset": 326,
+                "text": "That sounds great.",
+                "senderWorkerId": 1,
+                "messageId": 1051
+            },
+            {
+                "timeOffset": 379,
+                "text": "It is. You like blood and gore movies? If so, you might like @128905 .",
+                "senderWorkerId": 2,
+                "messageId": 1052
+            },
+            {
+                "timeOffset": 418,
+                "text": "No I do not like that genre of movie. The star wars movie is perfect for me.",
+                "senderWorkerId": 1,
+                "messageId": 1053
+            },
+            {
+                "timeOffset": 462,
+                "text": "You not a @145455 fan are you? Those films creep me out.",
+                "senderWorkerId": 2,
+                "messageId": 1054
+            },
+            {
+                "timeOffset": 521,
+                "text": "I found the movie I would like to watch. Thanks for all the help.",
+                "senderWorkerId": 1,
+                "messageId": 1055
+            },
+            {
+                "timeOffset": 545,
+                "text": "Oh okay. @152242 was a good tech film if you're into that genre.",
+                "senderWorkerId": 2,
+                "messageId": 1056
+            },
+            {
+                "timeOffset": 570,
+                "text": "How do we submit?",
+                "senderWorkerId": 2,
+                "messageId": 1057
+            },
+            {
+                "timeOffset": 609,
+                "text": "click the hide/show movie forms and fill the movie questions rows then it will let you submit.",
+                "senderWorkerId": 1,
+                "messageId": 1058
+            },
+            {
+                "timeOffset": 623,
+                "text": "I hope you have a great night. bye.",
+                "senderWorkerId": 1,
+                "messageId": 1059
+            },
+            {
+                "timeOffset": 628,
+                "text": "Thanks.",
+                "senderWorkerId": 2,
+                "messageId": 1060
+            }
+        ],
+        "conversationId": "395",
+        "respondentWorkerId": 1,
+        "initiatorWorkerId": 2,
+        "initiatorQuestions": []
+    },
+    {
+        "movieMentions": {
+            "79320": "Contact  (2009)",
+            "84001": "Donnie Darko (2001)",
+            "155969": "The Martian  (2015)",
+            "90950": "Avatar  (2009)",
+            "163606": "Avatar ",
+            "147598": "Indiana Jones and the Kingdom of the Crystal Skull (2008)",
+            "204292": "Star Wars"
+        },
+        "respondentQuestions": {
+            "79320": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "84001": {
+                "suggested": 1,
+                "seen": 1,
+                "liked": 1
+            },
+            "155969": {
+                "suggested": 1,
+                "seen": 1,
+                "liked": 1
+            },
+            "90950": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "163606": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "147598": {
+                "suggested": 0,
+                "seen": 0,
+                "liked": 1
+            },
+            "204292": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            }
+        },
+        "messages": [
+            {
+                "timeOffset": 0,
+                "text": "@163606 It is a nice movie. What say?",
+                "senderWorkerId": 3,
+                "messageId": 1061
+            },
+            {
+                "timeOffset": 31,
+                "text": "@90950 Was a marvelous 3D experience personally for me.",
+                "senderWorkerId": 3,
+                "messageId": 1062
+            },
+            {
+                "timeOffset": 56,
+                "text": "I really liked that movie but haven't seen it in a while. Are you a Michelle Rodriquez fan?",
+                "senderWorkerId": 1,
+                "messageId": 1063
+            },
+            {
+                "timeOffset": 110,
+                "text": "No. I am not. I like sci-fi movies. Have you watched @155969.",
+                "senderWorkerId": 3,
+                "messageId": 1064
+            },
+            {
+                "timeOffset": 146,
+                "text": "My another favorite sci-fi movies are @79320 and @84001.",
+                "senderWorkerId": 3,
+                "messageId": 1065
+            },
+            {
+                "timeOffset": 159,
+                "text": "No I have not seen that one but have seen all the @204292 movies. Do you like those.",
+                "senderWorkerId": 1,
+                "messageId": 1066
+            },
+            {
+                "timeOffset": 181,
+                "text": "Yes, I love @204292 series.",
+                "senderWorkerId": 3,
+                "messageId": 1067
+            },
+            {
+                "timeOffset": 206,
+                "text": "In fact I am excited about the upcoming @204292.",
+                "senderWorkerId": 3,
+                "messageId": 1068
+            },
+            {
+                "timeOffset": 231,
+                "text": "What are you favorite movies?",
+                "senderWorkerId": 3,
+                "messageId": 1069
+            },
+            {
+                "timeOffset": 249,
+                "text": "I am too I think you will like @147598.",
+                "senderWorkerId": 1,
+                "messageId": 1070
+            },
+            {
+                "timeOffset": 275,
+                "text": "I have not seen @147598.",
+                "senderWorkerId": 3,
+                "messageId": 1071
+            },
+            {
+                "timeOffset": 283,
+                "text": "I will watch it soon.",
+                "senderWorkerId": 3,
+                "messageId": 1072
+            },
+            {
+                "timeOffset": 312,
+                "text": "It is a good movie if you like Star wars you should like it.",
+                "senderWorkerId": 1,
+                "messageId": 1073
+            },
+            {
+                "timeOffset": 344,
+                "text": "Great. I will watch those. Now, let us submit this. Nice talking to you, have a nice day!",
+                "senderWorkerId": 3,
+                "messageId": 1074
+            },
+            {
+                "timeOffset": 361,
+                "text": "Thanks it was nice talking to you too bye.",
+                "senderWorkerId": 1,
+                "messageId": 1075
+            }
+        ],
+        "conversationId": "397",
+        "respondentWorkerId": 1,
+        "initiatorWorkerId": 3,
+        "initiatorQuestions": {
+            "79320": {
+                "suggested": 0,
+                "seen": 0,
+                "liked": 1
+            },
+            "84001": {
+                "suggested": 0,
+                "seen": 0,
+                "liked": 1
+            },
+            "155969": {
+                "suggested": 0,
+                "seen": 0,
+                "liked": 1
+            },
+            "90950": {
+                "suggested": 0,
+                "seen": 0,
+                "liked": 1
+            },
+            "163606": {
+                "suggested": 0,
+                "seen": 0,
+                "liked": 0
+            },
+            "147598": {
+                "suggested": 1,
+                "seen": 1,
+                "liked": 1
+            },
+            "204292": {
+                "suggested": 1,
+                "seen": 1,
+                "liked": 1
+            }
+        }
+    },
+    {
+        "movieMentions": {
+            "188302": "Ever After (1998)",
+            "195904": "Charlie's Angels ",
+            "91313": "Blended  (2014)",
+            "157394": "The Wedding Singer (1998)",
+            "115908": "50 First Dates (2004)"
+        },
+        "respondentQuestions": [],
+        "messages": [
+            {
+                "timeOffset": 0,
+                "text": "I'm in the mood to watch a romantic comedy.  What do you suggest?",
+                "senderWorkerId": 4,
+                "messageId": 1076
+            },
+            {
+                "timeOffset": 20,
+                "text": "@115908.",
+                "senderWorkerId": 5,
+                "messageId": 1077
+            },
+            {
+                "timeOffset": 36,
+                "text": "Have you seen that one?",
+                "senderWorkerId": 5,
+                "messageId": 1078
+            },
+            {
+                "timeOffset": 91,
+                "text": "Oh, I've seen that one.  I really like Drew Barrymore.",
+                "senderWorkerId": 4,
+                "messageId": 1079
+            },
+            {
+                "timeOffset": 144,
+                "text": "Yes she is good, I am looking for a super hero movie myself.",
+                "senderWorkerId": 5,
+                "messageId": 1080
+            },
+            {
+                "timeOffset": 169,
+                "text": "Do you like @157394.",
+                "senderWorkerId": 5,
+                "messageId": 1081
+            },
+            {
+                "timeOffset": 188,
+                "text": "Drew Barrymore was in @195904.  Do you think that counts as a superhero movie?",
+                "senderWorkerId": 4,
+                "messageId": 1082
+            },
+            {
+                "timeOffset": 199,
+                "text": "Yeah, definitely. I liked that one.",
+                "senderWorkerId": 5,
+                "messageId": 1083
+            },
+            {
+                "timeOffset": 300,
+                "text": "Oh, @157394 is a good one.  Sandler and Barrymore are great together.  I'm very excited to finally see @91313.",
+                "senderWorkerId": 4,
+                "messageId": 1084
+            },
+            {
+                "timeOffset": 320,
+                "text": "Oh I have heard good things about that film.",
+                "senderWorkerId": 5,
+                "messageId": 1085
+            },
+            {
+                "timeOffset": 358,
+                "text": "I also liked Barrymore in @188302.",
+                "senderWorkerId": 4,
+                "messageId": 1086
+            },
+            {
+                "timeOffset": 458,
+                "text": "That is one film I should definitely check out.",
+                "senderWorkerId": 5,
+                "messageId": 1090
+            }
+        ],
+        "conversationId": "405",
+        "respondentWorkerId": 5,
+        "initiatorWorkerId": 4,
+        "initiatorQuestions": []
+    },
+    {
+        "movieMentions": {
+            "119144": "Wonder Woman  (2017)",
+            "125431": "Annabelle  (2014)",
+            "141788": "Fast & Furious  (2009)",
+            "204331": "Girls Trip (2017)",
+            "184418": "Get Out (2017)",
+            "136632": "Spider-Man: Homecoming (2017)"
+        },
+        "respondentQuestions": {
+            "119144": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "125431": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "141788": {
+                "suggested": 1,
+                "seen": 1,
+                "liked": 1
+            },
+            "204331": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "184418": {
+                "suggested": 1,
+                "seen": 1,
+                "liked": 1
+            },
+            "136632": {
+                "suggested": 0,
+                "seen": 0,
+                "liked": 1
+            }
+        },
+        "messages": [
+            {
+                "timeOffset": 0,
+                "text": "Hello.",
+                "senderWorkerId": 6,
+                "messageId": 1087
+            },
+            {
+                "timeOffset": 24,
+                "text": "Hello.",
+                "senderWorkerId": 7,
+                "messageId": 1088
+            },
+            {
+                "timeOffset": 51,
+                "text": "What movie would you suggest to watch.",
+                "senderWorkerId": 7,
+                "messageId": 1089
+            },
+            {
+                "timeOffset": 116,
+                "text": "@184418.",
+                "senderWorkerId": 6,
+                "messageId": 1091
+            },
+            {
+                "timeOffset": 171,
+                "text": "Have you seen that movie before?",
+                "senderWorkerId": 6,
+                "messageId": 1092
+            },
+            {
+                "timeOffset": 171,
+                "text": "I love that scary movies. I love @125431.",
+                "senderWorkerId": 7,
+                "messageId": 1093
+            },
+            {
+                "timeOffset": 185,
+                "text": "Yes I love Annabelle as well.",
+                "senderWorkerId": 6,
+                "messageId": 1094
+            },
+            {
+                "timeOffset": 197,
+                "text": "That is a good movie.",
+                "senderWorkerId": 6,
+                "messageId": 1095
+            },
+            {
+                "timeOffset": 206,
+                "text": "I never knew a doll could be so scary.",
+                "senderWorkerId": 7,
+                "messageId": 1096
+            },
+            {
+                "timeOffset": 228,
+                "text": "Me either. But I love scary movies.",
+                "senderWorkerId": 6,
+                "messageId": 1097
+            },
+            {
+                "timeOffset": 237,
+                "text": "What other movies do you like to watch?",
+                "senderWorkerId": 6,
+                "messageId": 1098
+            },
+            {
+                "timeOffset": 312,
+                "text": "Funny movies! LIke @204331.",
+                "senderWorkerId": 7,
+                "messageId": 1099
+            },
+            {
+                "timeOffset": 319,
+                "text": "What about you.",
+                "senderWorkerId": 7,
+                "messageId": 1100
+            },
+            {
+                "timeOffset": 338,
+                "text": "Yes I love that movie. I never get tired of watching it.",
+                "senderWorkerId": 6,
+                "messageId": 1101
+            },
+            {
+                "timeOffset": 353,
+                "text": "I like certain action movies li-03i25.",
+                "senderWorkerId": 6,
+                "messageId": 1102
+            },
+            {
+                "timeOffset": 379,
+                "text": "I like certain action movies like @141788.",
+                "senderWorkerId": 6,
+                "messageId": 1103
+            },
+            {
+                "timeOffset": 419,
+                "text": "Me too! I love all those movies. I also like @119144.",
+                "senderWorkerId": 7,
+                "messageId": 1104
+            },
+            {
+                "timeOffset": 447,
+                "text": "Yes @119144 is a good movie too.",
+                "senderWorkerId": 6,
+                "messageId": 1105
+            },
+            {
+                "timeOffset": 486,
+                "text": "And also @136632.",
+                "senderWorkerId": 7,
+                "messageId": 1106
+            },
+            {
+                "timeOffset": 498,
+                "text": "I haven't seen that movie yet.",
+                "senderWorkerId": 6,
+                "messageId": 1107
+            }
+        ],
+        "conversationId": "407",
+        "respondentWorkerId": 6,
+        "initiatorWorkerId": 7,
+        "initiatorQuestions": {
+            "119144": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "125431": {
+                "suggested": 1,
+                "seen": 1,
+                "liked": 1
+            },
+            "141788": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "204331": {
+                "suggested": 1,
+                "seen": 1,
+                "liked": 1
+            },
+            "184418": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            },
+            "136632": {
+                "suggested": 0,
+                "seen": 1,
+                "liked": 1
+            }
+        }
+    }
+]

conversational-recommendation-dialogues/SalesBot/README.md

@@ -0,0 +1,57 @@
+# SalesBot: Transitioning from Chit-Chat to Task-Oriented Dialogues
+
+## Framework
+<p align="center">
+	<img src="img/framework.png" width="100%" />
+</p>
+This paper focuses on investigating the conversations starting from open-domain social chatting and then gradually transitioning to task-oriented purposes, and releases a large-scale dataset with detailed annotations for encouraging this research direction. To achieve this goal, this paper proposes a framework to automatically generate many dialogues without human involvement, in which any powerful open-domain dialogue generation model can be easily leveraged.
+
+## Dependency
+Check the packages needed or simply run the command
+```console
+conda env create -f environment.yml
+```
+
+## Data
+* selfchat:
+```console
+mkdir selfchat
+parlai self_chat --model-file zoo:blender/blender_1Bdistill/model --inference nucleus --num-self-chats 20 --task blended_skill_talk --include-personas True --include-initial-utterances True --outfile selfchat/merge_sgd_20.json
+parlai self_chat --model-file zoo:blender/blender_1Bdistill/model --inference nucleus --num-self-chats 20 --task blended_skill_talk --include-personas True --include-initial-utterances True --outfile selfchat/simulators_20.json
+```
+* intent detection model:
+```console
+python3 qa_inference.py --data_file selfchat/merge_sgd_20.jsonl --output_file merge_sgd_intent.json --device 0
+python3 qa_inference.py --data_file selfchat/simulators_20.jsonl --output_file simulators_intent.json --device 0
+```
+* task-oriented simulators:
+```console
+python3 combine_simulators.py simulators_intent.json
+```
+* merge SGD:
+```console
+# SGD_delex is the version preprocessed by "ACCENTOR: Adding Chit-Chat to Enhance Task-Oriented Dialogues"
+unzip SGD_delex
+mkdir sgd_intent_dialog
+python3 collect_sgd_intent.py SGD_delex
+python3 combine_sgd.py merge_sgd_intent.json
+
+```
+* transition:
+```console
+python3 transition.py combine_sgd.json
+python3 transition.py combine_simulators.json
+```
+
+## Citation
+
+Please cite our paper if you use SalesBot in your work:
+
+```bibtex
+@inproceedings{chiu2022salesbot,
+   title={{SalesBot}: Transitioning from Chit-Chat to Task-Oriented Dialogues},
+   author={Chiu, Ssu and Li, Maolin and Lin, Yen-Ting and Chen, Yun-Nung},
+   booktitle={Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL)},
+   year={2022}
+}
+```

conversational-recommendation-dialogues/SalesBot/converted_examples.json

@@ -0,0 +1,449 @@
+{
+    "SalesBot--train--1": {
+        "original dialog id": "simulateTOD_0001",
+        "dialog index": 1,
+        "original dialog info": {
+            "intent": {
+                "type": [
+                    "FindMovies"
+                ],
+                "position": 7
+            },
+            "transition_candidates": [
+                "Is there anything else I can do for you?",
+                "What do you think of the movie?",
+                "Are you planning on buying tickets now?",
+                "Could you please confirm that you like to play it. Can I tell you anything else? Is there anything else I can help you with?"
+            ]
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "It's a Toyota Corolla.  I love it.  How about you?",
+                "system response": "I drive a Honda Civic. It's the best car I've ever owned.",
+                "dialog history": "",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 2,
+                "user utterance": "I love Hondas.  They're so reliable.  Do you have any hobbies?",
+                "system response": "I like to write poetry and donate my old clothes. What do you like to do?",
+                "dialog history": "<USER> It's a Toyota Corolla.  I love it.  How about you? <SYSTEM> I drive a Honda Civic. It's the best car I've ever owned.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 3,
+                "user utterance": "I love to read Stephen King books.  He's one of my favorite authors.",
+                "system response": "I haven't read any of his books, but I've heard good things. What's your favorite book of his?",
+                "dialog history": "<USER> It's a Toyota Corolla.  I love it.  How about you? <SYSTEM> I drive a Honda Civic. It's the best car I've ever owned. <USER> I love Hondas.  They're so reliable.  Do you have any hobbies? <SYSTEM> I like to write poetry and donate my old clothes. What do you like to do?",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 4,
+                "user utterance": "My favorite of his is The Shining.  Have you seen the movie?  It came out in 1997.",
+                "system response": "I've seen it, but it's been so long that I don't remember much about it.",
+                "dialog history": "<USER> It's a Toyota Corolla.  I love it.  How about you? <SYSTEM> I drive a Honda Civic. It's the best car I've ever owned. <USER> I love Hondas.  They're so reliable.  Do you have any hobbies? <SYSTEM> I like to write poetry and donate my old clothes. What do you like to do? <USER> I love to read Stephen King books.  He's one of my favorite authors. <SYSTEM> I haven't read any of his books, but I've heard good things. What's your favorite book of his?",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 5,
+                "user utterance": "Is there anything else I can do for you?",
+                "system response": "Yes, I'd like to find an Adventure movie.",
+                "dialog history": "<USER> It's a Toyota Corolla.  I love it.  How about you? <SYSTEM> I drive a Honda Civic. It's the best car I've ever owned. <USER> I love Hondas.  They're so reliable.  Do you have any hobbies? <SYSTEM> I like to write poetry and donate my old clothes. What do you like to do? <USER> I love to read Stephen King books.  He's one of my favorite authors. <SYSTEM> I haven't read any of his books, but I've heard good things. What's your favorite book of his? <USER> My favorite of his is The Shining.  Have you seen the movie?  It came out in 1997. <SYSTEM> I've seen it, but it's been so long that I don't remember much about it.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 6,
+                "user utterance": "I found [count] movie you might like. How about [title]?",
+                "system response": "The Aftermath sounds great. That's all I need for now.",
+                "dialog history": "<USER> It's a Toyota Corolla.  I love it.  How about you? <SYSTEM> I drive a Honda Civic. It's the best car I've ever owned. <USER> I love Hondas.  They're so reliable.  Do you have any hobbies? <SYSTEM> I like to write poetry and donate my old clothes. What do you like to do? <USER> I love to read Stephen King books.  He's one of my favorite authors. <SYSTEM> I haven't read any of his books, but I've heard good things. What's your favorite book of his? <USER> My favorite of his is The Shining.  Have you seen the movie?  It came out in 1997. <SYSTEM> I've seen it, but it's been so long that I don't remember much about it. <USER> Is there anything else I can do for you? <SYSTEM> Yes, I'd like to find an Adventure movie.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 7,
+                "user utterance": "Okay, have a great day. I hope you enjoy the movie. Bye.!.",
+                "system response": "",
+                "dialog history": "<USER> It's a Toyota Corolla.  I love it.  How about you? <SYSTEM> I drive a Honda Civic. It's the best car I've ever owned. <USER> I love Hondas.  They're so reliable.  Do you have any hobbies? <SYSTEM> I like to write poetry and donate my old clothes. What do you like to do? <USER> I love to read Stephen King books.  He's one of my favorite authors. <SYSTEM> I haven't read any of his books, but I've heard good things. What's your favorite book of his? <USER> My favorite of his is The Shining.  Have you seen the movie?  It came out in 1997. <SYSTEM> I've seen it, but it's been so long that I don't remember much about it. <USER> Is there anything else I can do for you? <SYSTEM> Yes, I'd like to find an Adventure movie. <USER> I found [count] movie you might like. How about [title]? <SYSTEM> The Aftermath sounds great. That's all I need for now.",
+                "original user side information": {},
+                "original system side information": {}
+            }
+        ],
+        "external knowledge non-flat": {
+            "metadata": {},
+            "slots and values": {},
+            "intents": {}
+        },
+        "external knowledge": "",
+        "dst knowledge": "",
+        "intent knowledge": "",
+        "prompt": [
+            "This is a bot helping users to find a tourist attraction. Given the dialog context and external database, please generate a relevant system response for the user.",
+            "This bot assists users to find a tourist attraction. Based on the dialogue context and information from the external database, please generate an appropriate response for the user.",
+            "This bot helps users to find a tourist attraction. Provide a suitable response to the user, keeping in mind the conversation history and accessible external data.",
+            "The purpose of this bot is to assist users to find a tourist attraction. Considering the dialogue context and the information available in the external knowledge, please provide a fitting response for the user.",
+            "This bot is designed to help users find a tourist attraction. By utilizing the current dialog context and external resources, generate an appropriate response for the user."
+        ]
+    },
+    "SalesBot--train--2": {
+        "original dialog id": "simulateTOD_0002",
+        "dialog index": 2,
+        "original dialog info": {
+            "intent": {
+                "type": [
+                    "FindAttractions"
+                ],
+                "position": 1
+            },
+            "transition_candidates": [
+                "Where would you like to surf?",
+                "What is your favorite city on your calendar?",
+                "What is your location? I found [count] beaches that may be your closest. There are [count] beaches. What do you think about that?",
+                "No, I would recommend a good place for you to search, or a beach you like?"
+            ]
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "I'm going surfing. I love it. What do you like to do on your free time?",
+                "system response": "I like to garden and spend time with my family. Do you have a favorite place to surf?",
+                "dialog history": "",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 2,
+                "user utterance": "Where would you like to surf?",
+                "system response": "I'd like to find a garden in San Francisco.",
+                "dialog history": "<USER> I'm going surfing. I love it. What do you like to do on your free time? <SYSTEM> I like to garden and spend time with my family. Do you have a favorite place to surf?",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 3,
+                "user utterance": "I found [count] attractions you might like. How about a park called [attraction_name]?",
+                "system response": "Sure, that sounds good.",
+                "dialog history": "<USER> I'm going surfing. I love it. What do you like to do on your free time? <SYSTEM> I like to garden and spend time with my family. Do you have a favorite place to surf? <USER> Where would you like to surf? <SYSTEM> I'd like to find a garden in San Francisco.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 4,
+                "user utterance": "You should check out the [category] known as the park, called the Attractionname.",
+                "system response": "Okay, great. That's all I need for now.",
+                "dialog history": "<USER> I'm going surfing. I love it. What do you like to do on your free time? <SYSTEM> I like to garden and spend time with my family. Do you have a favorite place to surf? <USER> Where would you like to surf? <SYSTEM> I'd like to find a garden in San Francisco. <USER> I found [count] attractions you might like. How about a park called [attraction_name]? <SYSTEM> Sure, that sounds good.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 5,
+                "user utterance": "Okay, have a nice day. Goodbye for the day. Bye for now!",
+                "system response": "",
+                "dialog history": "<USER> I'm going surfing. I love it. What do you like to do on your free time? <SYSTEM> I like to garden and spend time with my family. Do you have a favorite place to surf? <USER> Where would you like to surf? <SYSTEM> I'd like to find a garden in San Francisco. <USER> I found [count] attractions you might like. How about a park called [attraction_name]? <SYSTEM> Sure, that sounds good. <USER> You should check out the [category] known as the park, called the Attractionname. <SYSTEM> Okay, great. That's all I need for now.",
+                "original user side information": {},
+                "original system side information": {}
+            }
+        ],
+        "external knowledge non-flat": {
+            "metadata": {},
+            "slots and values": {},
+            "intents": {}
+        },
+        "external knowledge": "",
+        "dst knowledge": "",
+        "intent knowledge": "",
+        "prompt": [
+            "This is a bot helping users to find a movie to watch. Given the dialog context and external database, please generate a relevant system response for the user.",
+            "This bot assists users to find a movie to watch. Based on the dialogue context and information from the external database, please generate an appropriate response for the user.",
+            "This bot helps users to find a movie to watch. Provide a suitable response to the user, keeping in mind the conversation history and accessible external data.",
+            "The purpose of this bot is to assist users to find a movie to watch. Considering the dialogue context and the information available in the external knowledge, please provide a fitting response for the user.",
+            "This bot is designed to help users find a movie to watch. By utilizing the current dialog context and external resources, generate an appropriate response for the user."
+        ]
+    },
+    "SalesBot--train--3": {
+        "original dialog id": "simulateTOD_0004",
+        "dialog index": 3,
+        "original dialog info": {
+            "intent": {
+                "type": [
+                    "PlaySong"
+                ],
+                "position": 5
+            },
+            "transition_candidates": [
+                "You may like to play the title in your kitchen. Do you like to play the title on the soundboard?",
+                "I've recently played it. You might like [event_name], [event_name] or [event_name]?",
+                "It was played in a kitchen game.",
+                "I've just started playing the game, though I haven't played it. I haven't. I am also playing the game."
+            ]
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "No, I've never played any of those. I'm more of an Xbox gamer myself.",
+                "system response": "I used to play a lot of video games when I was younger, but I haven't in a while.",
+                "dialog history": "",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 2,
+                "user utterance": "What kind of games do you like to play? I'm a big fan of first-person shooters.",
+                "system response": "I like first person shooters as well. I also like RPGs and adventure games.",
+                "dialog history": "<USER> No, I've never played any of those. I'm more of an Xbox gamer myself. <SYSTEM> I used to play a lot of video games when I was younger, but I haven't in a while.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 3,
+                "user utterance": "Adventure games are fun. Do you have a favorite adventure game that you've played recently?",
+                "system response": "I recently played the Legend of Zelda: Breath of the Wild. Have you played it?",
+                "dialog history": "<USER> No, I've never played any of those. I'm more of an Xbox gamer myself. <SYSTEM> I used to play a lot of video games when I was younger, but I haven't in a while. <USER> What kind of games do you like to play? I'm a big fan of first-person shooters. <SYSTEM> I like first person shooters as well. I also like RPGs and adventure games.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 4,
+                "user utterance": "You may like to play the title in your kitchen. Do you like to play the title on the soundboard?",
+                "system response": "Yeah, I'd like to play it on the speaker in the kitchen.",
+                "dialog history": "<USER> No, I've never played any of those. I'm more of an Xbox gamer myself. <SYSTEM> I used to play a lot of video games when I was younger, but I haven't in a while. <USER> What kind of games do you like to play? I'm a big fan of first-person shooters. <SYSTEM> I like first person shooters as well. I also like RPGs and adventure games. <USER> Adventure games are fun. Do you have a favorite adventure game that you've played recently? <SYSTEM> I recently played the Legend of Zelda: Breath of the Wild. Have you played it?",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 5,
+                "user utterance": "Please confirm: playing [song_name] on the [playback_device].",
+                "system response": "Yes, that's right.",
+                "dialog history": "<USER> No, I've never played any of those. I'm more of an Xbox gamer myself. <SYSTEM> I used to play a lot of video games when I was younger, but I haven't in a while. <USER> What kind of games do you like to play? I'm a big fan of first-person shooters. <SYSTEM> I like first person shooters as well. I also like RPGs and adventure games. <USER> Adventure games are fun. Do you have a favorite adventure game that you've played recently? <SYSTEM> I recently played the Legend of Zelda: Breath of the Wild. Have you played it? <USER> You may like to play the title in your kitchen. Do you like to play the title on the soundboard? <SYSTEM> Yeah, I'd like to play it on the speaker in the kitchen.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 6,
+                "user utterance": "Okay, so you want to play [title] with no subtitles?",
+                "system response": "Yes, please. Who directed it?",
+                "dialog history": "<USER> No, I've never played any of those. I'm more of an Xbox gamer myself. <SYSTEM> I used to play a lot of video games when I was younger, but I haven't in a while. <USER> What kind of games do you like to play? I'm a big fan of first-person shooters. <SYSTEM> I like first person shooters as well. I also like RPGs and adventure games. <USER> Adventure games are fun. Do you have a favorite adventure game that you've played recently? <SYSTEM> I recently played the Legend of Zelda: Breath of the Wild. Have you played it? <USER> You may like to play the title in your kitchen. Do you like to play the title on the soundboard? <SYSTEM> Yeah, I'd like to play it on the speaker in the kitchen. <USER> Please confirm: playing [song_name] on the [playback_device]. <SYSTEM> Yes, that's right.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 7,
+                "user utterance": "[directed_by] is the director. I will start the movie now.",
+                "system response": "Thank you. That's all I need.",
+                "dialog history": "<USER> No, I've never played any of those. I'm more of an Xbox gamer myself. <SYSTEM> I used to play a lot of video games when I was younger, but I haven't in a while. <USER> What kind of games do you like to play? I'm a big fan of first-person shooters. <SYSTEM> I like first person shooters as well. I also like RPGs and adventure games. <USER> Adventure games are fun. Do you have a favorite adventure game that you've played recently? <SYSTEM> I recently played the Legend of Zelda: Breath of the Wild. Have you played it? <USER> You may like to play the title in your kitchen. Do you like to play the title on the soundboard? <SYSTEM> Yeah, I'd like to play it on the speaker in the kitchen. <USER> Please confirm: playing [song_name] on the [playback_device]. <SYSTEM> Yes, that's right. <USER> Okay, so you want to play [title] with no subtitles? <SYSTEM> Yes, please. Who directed it?",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 8,
+                "user utterance": "You're welcome. Have a good day. Bye.  [title] is now playing.",
+                "system response": "",
+                "dialog history": "<USER> No, I've never played any of those. I'm more of an Xbox gamer myself. <SYSTEM> I used to play a lot of video games when I was younger, but I haven't in a while. <USER> What kind of games do you like to play? I'm a big fan of first-person shooters. <SYSTEM> I like first person shooters as well. I also like RPGs and adventure games. <USER> Adventure games are fun. Do you have a favorite adventure game that you've played recently? <SYSTEM> I recently played the Legend of Zelda: Breath of the Wild. Have you played it? <USER> You may like to play the title in your kitchen. Do you like to play the title on the soundboard? <SYSTEM> Yeah, I'd like to play it on the speaker in the kitchen. <USER> Please confirm: playing [song_name] on the [playback_device]. <SYSTEM> Yes, that's right. <USER> Okay, so you want to play [title] with no subtitles? <SYSTEM> Yes, please. Who directed it? <USER> [directed_by] is the director. I will start the movie now. <SYSTEM> Thank you. That's all I need.",
+                "original user side information": {},
+                "original system side information": {}
+            }
+        ],
+        "external knowledge non-flat": {
+            "metadata": {},
+            "slots and values": {},
+            "intents": {}
+        },
+        "external knowledge": "",
+        "dst knowledge": "",
+        "intent knowledge": "",
+        "prompt": [
+            "This is a bot helping users to find a tourist attraction. Given the dialog context and external database, please generate a relevant system response for the user.",
+            "This bot assists users to find a tourist attraction. Based on the dialogue context and information from the external database, please generate an appropriate response for the user.",
+            "This bot helps users to find a tourist attraction. Provide a suitable response to the user, keeping in mind the conversation history and accessible external data.",
+            "The purpose of this bot is to assist users to find a tourist attraction. Considering the dialogue context and the information available in the external knowledge, please provide a fitting response for the user.",
+            "This bot is designed to help users find a tourist attraction. By utilizing the current dialog context and external resources, generate an appropriate response for the user."
+        ]
+    },
+    "SalesBot--train--4": {
+        "original dialog id": "simulateTOD_0005",
+        "dialog index": 4,
+        "original dialog info": {
+            "intent": {
+                "type": [
+                    "FindAttractions"
+                ],
+                "position": 2
+            },
+            "transition_candidates": [
+                "What do you do for a trip? Whenever you do, you would like to go to New York to visit the famous attractions.",
+                "There's a certain trip I would recommend. Is that a trip of interest to a different city?",
+                "I found [count] places to visit. What about you? A nice trip to [destination]. You would have a trip to [destination]. What are you looking for? You'd like to see a visit to [attraction_name].",
+                "So you want to travel.. you have never been to the place."
+            ]
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "I would love to read it.  I love hiking.  What else do you like to do?",
+                "system response": "I like to hike too. I also like to travel. I've been to Ireland and Australia.",
+                "dialog history": "",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 2,
+                "user utterance": "I have never been to either of those places.  Have you ever been to New Zealand?",
+                "system response": "What do you do for a trip? Whenever you do, you would like to go to New York to visit the famous attractions.",
+                "dialog history": "<USER> I would love to read it.  I love hiking.  What else do you like to do? <SYSTEM> I like to hike too. I also like to travel. I've been to Ireland and Australia.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 3,
+                "user utterance": "Yes, I want to go to New York City. I'd like to visit some attractions there.",
+                "system response": "I found [count] attractions for you. How about the [attraction_name]? It's a [category].",
+                "dialog history": "<USER> I would love to read it.  I love hiking.  What else do you like to do? <SYSTEM> I like to hike too. I also like to travel. I've been to Ireland and Australia. <USER> I have never been to either of those places.  Have you ever been to New Zealand? <SYSTEM> What do you do for a trip? Whenever you do, you would like to go to New York to visit the famous attractions.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 4,
+                "user utterance": "Okay, that sounds good.",
+                "system response": "Okay, let's confirm the details: You want me to go to [event_location] on [date] at [time], and you want [party_size] people.",
+                "dialog history": "<USER> I would love to read it.  I love hiking.  What else do you like to do? <SYSTEM> I like to hike too. I also like to travel. I've been to Ireland and Australia. <USER> I have never been to either of those places.  Have you ever been to New Zealand? <SYSTEM> What do you do for a trip? Whenever you do, you would like to go to New York to visit the famous attractions. <USER> Yes, I want to go to New York City. I'd like to visit some attractions there. <SYSTEM> I found [count] attractions for you. How about the [attraction_name]? It's a [category].",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 5,
+                "user utterance": "Yes, that's right.",
+                "system response": "I'll play [song_name] on the [playback_device], is that okay?",
+                "dialog history": "<USER> I would love to read it.  I love hiking.  What else do you like to do? <SYSTEM> I like to hike too. I also like to travel. I've been to Ireland and Australia. <USER> I have never been to either of those places.  Have you ever been to New Zealand? <SYSTEM> What do you do for a trip? Whenever you do, you would like to go to New York to visit the famous attractions. <USER> Yes, I want to go to New York City. I'd like to visit some attractions there. <SYSTEM> I found [count] attractions for you. How about the [attraction_name]? It's a [category]. <USER> Okay, that sounds good. <SYSTEM> Okay, let's confirm the details: You want me to go to [event_location] on [date] at [time], and you want [party_size] people.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 6,
+                "user utterance": "Yes, please do.",
+                "system response": "Sure, please confirm your request to play [title] with no subtitles.",
+                "dialog history": "<USER> I would love to read it.  I love hiking.  What else do you like to do? <SYSTEM> I like to hike too. I also like to travel. I've been to Ireland and Australia. <USER> I have never been to either of those places.  Have you ever been to New Zealand? <SYSTEM> What do you do for a trip? Whenever you do, you would like to go to New York to visit the famous attractions. <USER> Yes, I want to go to New York City. I'd like to visit some attractions there. <SYSTEM> I found [count] attractions for you. How about the [attraction_name]? It's a [category]. <USER> Okay, that sounds good. <SYSTEM> Okay, let's confirm the details: You want me to go to [event_location] on [date] at [time], and you want [party_size] people. <USER> Yes, that's right. <SYSTEM> I'll play [song_name] on the [playback_device], is that okay?",
+                "original user side information": {},
+                "original system side information": {}
+            }
+        ],
+        "external knowledge non-flat": {
+            "metadata": {},
+            "slots and values": {},
+            "intents": {}
+        },
+        "external knowledge": "",
+        "dst knowledge": "",
+        "intent knowledge": "",
+        "prompt": [
+            "This is a bot helping users to find and play a song. Given the dialog context and external database, please generate a relevant system response for the user.",
+            "This bot assists users to find and play a song. Based on the dialogue context and information from the external database, please generate an appropriate response for the user.",
+            "This bot helps users to find and play a song. Provide a suitable response to the user, keeping in mind the conversation history and accessible external data.",
+            "The purpose of this bot is to assist users to find and play a song. Considering the dialogue context and the information available in the external knowledge, please provide a fitting response for the user.",
+            "This bot is designed to help users find and play a song. By utilizing the current dialog context and external resources, generate an appropriate response for the user."
+        ]
+    },
+    "SalesBot--train--5": {
+        "original dialog id": "simulateTOD_0006",
+        "dialog index": 5,
+        "original dialog info": {
+            "intent": {
+                "type": [
+                    "FindMovies"
+                ],
+                "position": 5
+            },
+            "transition_candidates": [
+                "Are you looking for another movie?",
+                "Do you have any other hobbies?",
+                "Do you like movies? I like to watch them. I like to watch them in real time. I like watching them.",
+                "Is there anything else I can help you with?"
+            ]
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "I'm sorry to hear that. Do you have any other pets that you can take with you?",
+                "system response": "I don't have any pets right now, but I used to have a dog when I was younger.",
+                "dialog history": "",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 2,
+                "user utterance": "Oh, I see. What kind of dog did you have when you were younger? I love dogs!",
+                "system response": "I had a Labrador Retriever. He was the best dog ever.",
+                "dialog history": "<USER> I'm sorry to hear that. Do you have any other pets that you can take with you? <SYSTEM> I don't have any pets right now, but I used to have a dog when I was younger.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 3,
+                "user utterance": "Aww, I love labradors! They're so sweet and gentle. What do you like to do for fun?",
+                "system response": "I like to watch movies and play video games. I also like to read. What about you?",
+                "dialog history": "<USER> I'm sorry to hear that. Do you have any other pets that you can take with you? <SYSTEM> I don't have any pets right now, but I used to have a dog when I was younger. <USER> Oh, I see. What kind of dog did you have when you were younger? I love dogs! <SYSTEM> I had a Labrador Retriever. He was the best dog ever.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 4,
+                "user utterance": "Are you looking for another movie?",
+                "system response": "I really like fantasy movies. I'd like to find something directed by Hiroyasu Ishida.",
+                "dialog history": "<USER> I'm sorry to hear that. Do you have any other pets that you can take with you? <SYSTEM> I don't have any pets right now, but I used to have a dog when I was younger. <USER> Oh, I see. What kind of dog did you have when you were younger? I love dogs! <SYSTEM> I had a Labrador Retriever. He was the best dog ever. <USER> Aww, I love labradors! They're so sweet and gentle. What do you like to do for fun? <SYSTEM> I like to watch movies and play video games. I also like to read. What about you?",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 5,
+                "user utterance": "I found [count] movie you might like. How about [title]?",
+                "system response": "The Poseidon Adventure sounds great. I want to watch it now.",
+                "dialog history": "<USER> I'm sorry to hear that. Do you have any other pets that you can take with you? <SYSTEM> I don't have any pets right now, but I used to have a dog when I was younger. <USER> Oh, I see. What kind of dog did you have when you were younger? I love dogs! <SYSTEM> I had a Labrador Retriever. He was the best dog ever. <USER> Aww, I love labradors! They're so sweet and gentle. What do you like to do for fun? <SYSTEM> I like to watch movies and play video games. I also like to read. What about you? <USER> Are you looking for another movie? <SYSTEM> I really like fantasy movies. I'd like to find something directed by Hiroyasu Ishida.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 6,
+                "user utterance": "Please confirm the following: Play the movie titled Poseodon with subtitles.",
+                "system response": "Yes, that's right.",
+                "dialog history": "<USER> I'm sorry to hear that. Do you have any other pets that you can take with you? <SYSTEM> I don't have any pets right now, but I used to have a dog when I was younger. <USER> Oh, I see. What kind of dog did you have when you were younger? I love dogs! <SYSTEM> I had a Labrador Retriever. He was the best dog ever. <USER> Aww, I love labradors! They're so sweet and gentle. What do you like to do for fun? <SYSTEM> I like to watch movies and play video games. I also like to read. What about you? <USER> Are you looking for another movie? <SYSTEM> I really like fantasy movies. I'd like to find something directed by Hiroyasu Ishida. <USER> I found [count] movie you might like. How about [title]? <SYSTEM> The Poseidon Adventure sounds great. I want to watch it now.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 7,
+                "user utterance": "Please confirm: Playing [title] with sub titles: Enjoy the movie.",
+                "system response": "Yes, thank you.",
+                "dialog history": "<USER> I'm sorry to hear that. Do you have any other pets that you can take with you? <SYSTEM> I don't have any pets right now, but I used to have a dog when I was younger. <USER> Oh, I see. What kind of dog did you have when you were younger? I love dogs! <SYSTEM> I had a Labrador Retriever. He was the best dog ever. <USER> Aww, I love labradors! They're so sweet and gentle. What do you like to do for fun? <SYSTEM> I like to watch movies and play video games. I also like to read. What about you? <USER> Are you looking for another movie? <SYSTEM> I really like fantasy movies. I'd like to find something directed by Hiroyasu Ishida. <USER> I found [count] movie you might like. How about [title]? <SYSTEM> The Poseidon Adventure sounds great. I want to watch it now. <USER> Please confirm the following: Play the movie titled Poseodon with subtitles. <SYSTEM> Yes, that's right.",
+                "original user side information": {},
+                "original system side information": {}
+            },
+            {
+                "turn id": 8,
+                "user utterance": "The movie has started playing. Enjoy your movie. Hope you enjoy the same. Bye.",
+                "system response": "",
+                "dialog history": "<USER> I'm sorry to hear that. Do you have any other pets that you can take with you? <SYSTEM> I don't have any pets right now, but I used to have a dog when I was younger. <USER> Oh, I see. What kind of dog did you have when you were younger? I love dogs! <SYSTEM> I had a Labrador Retriever. He was the best dog ever. <USER> Aww, I love labradors! They're so sweet and gentle. What do you like to do for fun? <SYSTEM> I like to watch movies and play video games. I also like to read. What about you? <USER> Are you looking for another movie? <SYSTEM> I really like fantasy movies. I'd like to find something directed by Hiroyasu Ishida. <USER> I found [count] movie you might like. How about [title]? <SYSTEM> The Poseidon Adventure sounds great. I want to watch it now. <USER> Please confirm the following: Play the movie titled Poseodon with subtitles. <SYSTEM> Yes, that's right. <USER> Please confirm: Playing [title] with sub titles: Enjoy the movie. <SYSTEM> Yes, thank you.",
+                "original user side information": {},
+                "original system side information": {}
+            }
+        ],
+        "external knowledge non-flat": {
+            "metadata": {},
+            "slots and values": {},
+            "intents": {}
+        },
+        "external knowledge": "",
+        "dst knowledge": "",
+        "intent knowledge": "",
+        "prompt": [
+            "This is a bot helping users to find a tourist attraction. Given the dialog context and external database, please generate a relevant system response for the user.",
+            "This bot assists users to find a tourist attraction. Based on the dialogue context and information from the external database, please generate an appropriate response for the user.",
+            "This bot helps users to find a tourist attraction. Provide a suitable response to the user, keeping in mind the conversation history and accessible external data.",
+            "The purpose of this bot is to assist users to find a tourist attraction. Considering the dialogue context and the information available in the external knowledge, please provide a fitting response for the user.",
+            "This bot is designed to help users find a tourist attraction. By utilizing the current dialog context and external resources, generate an appropriate response for the user."
+        ]
+    }
+}

conversational-recommendation-dialogues/SalesBot/original_examples.json

@@ -0,0 +1,156 @@
+[
+    {
+        "id": "simulateTOD_0001",
+        "dialog": [
+            "It's a Toyota Corolla.  I love it.  How about you?",
+            "I drive a Honda Civic. It's the best car I've ever owned.",
+            "I love Hondas.  They're so reliable.  Do you have any hobbies?",
+            "I like to write poetry and donate my old clothes. What do you like to do?",
+            "I love to read Stephen King books.  He's one of my favorite authors.",
+            "I haven't read any of his books, but I've heard good things. What's your favorite book of his?",
+            "My favorite of his is The Shining.  Have you seen the movie?  It came out in 1997.",
+            "I've seen it, but it's been so long that I don't remember much about it.",
+            "Is there anything else I can do for you?",
+            "Yes, I'd like to find an Adventure movie.",
+            "I found [count] movie you might like. How about [title]?",
+            "The Aftermath sounds great. That's all I need for now.",
+            "Okay, have a great day. I hope you enjoy the movie. Bye.!."
+        ],
+        "intent": {
+            "type": [
+                "FindMovies"
+            ],
+            "position": 7
+        },
+        "transition_candidates": [
+            "Is there anything else I can do for you?",
+            "What do you think of the movie?",
+            "Are you planning on buying tickets now?",
+            "Could you please confirm that you like to play it. Can I tell you anything else? Is there anything else I can help you with?"
+        ],
+        "filename": "TOD_Simulators"
+    },
+    {
+        "id": "simulateTOD_0002",
+        "dialog": [
+            "I'm going surfing. I love it. What do you like to do on your free time?",
+            "I like to garden and spend time with my family. Do you have a favorite place to surf?",
+            "Where would you like to surf?",
+            "I'd like to find a garden in San Francisco.",
+            "I found [count] attractions you might like. How about a park called [attraction_name]?",
+            "Sure, that sounds good.",
+            "You should check out the [category] known as the park, called the Attractionname.",
+            "Okay, great. That's all I need for now.",
+            "Okay, have a nice day. Goodbye for the day. Bye for now!"
+        ],
+        "intent": {
+            "type": [
+                "FindAttractions"
+            ],
+            "position": 1
+        },
+        "transition_candidates": [
+            "Where would you like to surf?",
+            "What is your favorite city on your calendar?",
+            "What is your location? I found [count] beaches that may be your closest. There are [count] beaches. What do you think about that?",
+            "No, I would recommend a good place for you to search, or a beach you like?"
+        ],
+        "filename": "TOD_Simulators"
+    },
+    {
+        "id": "simulateTOD_0004",
+        "dialog": [
+            "No, I've never played any of those. I'm more of an Xbox gamer myself.",
+            "I used to play a lot of video games when I was younger, but I haven't in a while.",
+            "What kind of games do you like to play? I'm a big fan of first-person shooters.",
+            "I like first person shooters as well. I also like RPGs and adventure games.",
+            "Adventure games are fun. Do you have a favorite adventure game that you've played recently?",
+            "I recently played the Legend of Zelda: Breath of the Wild. Have you played it?",
+            "You may like to play the title in your kitchen. Do you like to play the title on the soundboard?",
+            "Yeah, I'd like to play it on the speaker in the kitchen.",
+            "Please confirm: playing [song_name] on the [playback_device].",
+            "Yes, that's right.",
+            "Okay, so you want to play [title] with no subtitles?",
+            "Yes, please. Who directed it?",
+            "[directed_by] is the director. I will start the movie now.",
+            "Thank you. That's all I need.",
+            "You're welcome. Have a good day. Bye.  [title] is now playing."
+        ],
+        "intent": {
+            "type": [
+                "PlaySong"
+            ],
+            "position": 5
+        },
+        "transition_candidates": [
+            "You may like to play the title in your kitchen. Do you like to play the title on the soundboard?",
+            "I've recently played it. You might like [event_name], [event_name] or [event_name]?",
+            "It was played in a kitchen game.",
+            "I've just started playing the game, though I haven't played it. I haven't. I am also playing the game."
+        ],
+        "filename": "TOD_Simulators"
+    },
+    {
+        "id": "simulateTOD_0005",
+        "dialog": [
+            "I would love to read it.  I love hiking.  What else do you like to do?",
+            "I like to hike too. I also like to travel. I've been to Ireland and Australia.",
+            "I have never been to either of those places.  Have you ever been to New Zealand?",
+            "What do you do for a trip? Whenever you do, you would like to go to New York to visit the famous attractions.",
+            "Yes, I want to go to New York City. I'd like to visit some attractions there.",
+            "I found [count] attractions for you. How about the [attraction_name]? It's a [category].",
+            "Okay, that sounds good.",
+            "Okay, let's confirm the details: You want me to go to [event_location] on [date] at [time], and you want [party_size] people.",
+            "Yes, that's right.",
+            "I'll play [song_name] on the [playback_device], is that okay?",
+            "Yes, please do.",
+            "Sure, please confirm your request to play [title] with no subtitles."
+        ],
+        "intent": {
+            "type": [
+                "FindAttractions"
+            ],
+            "position": 2
+        },
+        "transition_candidates": [
+            "What do you do for a trip? Whenever you do, you would like to go to New York to visit the famous attractions.",
+            "There's a certain trip I would recommend. Is that a trip of interest to a different city?",
+            "I found [count] places to visit. What about you? A nice trip to [destination]. You would have a trip to [destination]. What are you looking for? You'd like to see a visit to [attraction_name].",
+            "So you want to travel.. you have never been to the place."
+        ],
+        "filename": "TOD_Simulators"
+    },
+    {
+        "id": "simulateTOD_0006",
+        "dialog": [
+            "I'm sorry to hear that. Do you have any other pets that you can take with you?",
+            "I don't have any pets right now, but I used to have a dog when I was younger.",
+            "Oh, I see. What kind of dog did you have when you were younger? I love dogs!",
+            "I had a Labrador Retriever. He was the best dog ever.",
+            "Aww, I love labradors! They're so sweet and gentle. What do you like to do for fun?",
+            "I like to watch movies and play video games. I also like to read. What about you?",
+            "Are you looking for another movie?",
+            "I really like fantasy movies. I'd like to find something directed by Hiroyasu Ishida.",
+            "I found [count] movie you might like. How about [title]?",
+            "The Poseidon Adventure sounds great. I want to watch it now.",
+            "Please confirm the following: Play the movie titled Poseodon with subtitles.",
+            "Yes, that's right.",
+            "Please confirm: Playing [title] with sub titles: Enjoy the movie.",
+            "Yes, thank you.",
+            "The movie has started playing. Enjoy your movie. Hope you enjoy the same. Bye."
+        ],
+        "intent": {
+            "type": [
+                "FindMovies"
+            ],
+            "position": 5
+        },
+        "transition_candidates": [
+            "Are you looking for another movie?",
+            "Do you have any other hobbies?",
+            "Do you like movies? I like to watch them. I like to watch them in real time. I like watching them.",
+            "Is there anything else I can help you with?"
+        ],
+        "filename": "TOD_Simulators"
+    }
+]

conversational-recommendation-dialogues/SalesBot/otgy.json

@@ -0,0 +1,8 @@
+[
+    "GetTimesForMovie",
+    "LookupSong",
+    "FindMovies",
+    "LookupMusic",
+    "PlaySong",
+    "FindAttractions"
+]

dialogstudio.py

@@ -0,0 +1,284 @@
+"""
+ Copyright (c) 2023, salesforce.com, inc.
+ All rights reserved.
+ SPDX-License-Identifier: Apache License 2.0
+ For full license text, see the LICENSE file in the repo root or https://www.apache.org/licenses/LICENSE-2.0
+"""
+
+
+#!/usr/bin/env python3
+import os
+import json
+import datasets
+from datasets import (GeneratorBasedBuilder,
+                        BuilderConfig,
+                        SplitGenerator, 
+                        DatasetInfo, 
+                        Features,
+                        Sequence,
+                        Value,
+                        Version)
+
+logger = datasets.logging.get_logger(__name__)
+datasets.logging.disable_progress_bar()
+
+_VERSION = Version("1.0.0")
+_CITATION = """
+    @misc{zhang2023dialogstudio,
+    title={DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI}, 
+    author={Jianguo Zhang and Kun Qian and Zhiwei Liu and Shelby Heinecke and Rui Meng and Ye Liu and Zhou Yu and and Huan Wang and Silvio Savarese and Caiming Xiong},
+    year={2023},
+    eprint={2307.10172},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+"""
+
+DATASETS = {
+    # not pass: "CANARD"
+    "open_domain": [
+                        "chitchat-dataset", "ConvAI2", "AntiScam", "Empathetic", "HH-RLHF", 
+                        "PLACES3.5", "Prosocial", "SODA"
+                    ],
+    "knowledge_grounded": [
+                        "CompWebQ", "CoQA", "CoSQL", "DART", "FeTaQA", 
+                        "GrailQA", "HybridQA", "MTOP", "MultiModalQA", "SParC", 
+                        "Spider", "SQA", "ToTTo", "WebQSP", "WikiSQL", 
+                        "WikiTQ", "wizard_of_internet", "wizard_of_wikipedia"
+                    ],
+    "dialogue_summarization": [
+                        "AMI", "CRD3", "DialogSum", "ECTSum", "ICSI", 
+                        "MediaSum", "QMSum", "SAMSum", "TweetSumm", "ConvoSumm", 
+                        "SummScreen_ForeverDreaming", "SummScreen_TVMegaSite"
+                    ],
+    "natural_language_understanding": [
+                        "ATIS", "ATIS-NER", "BANKING77", "BANKING77-OOS", "CLINC-Single-Domain-OOS-banking", 
+                        "CLINC-Single-Domain-OOS-credit_cards", "CLINC150", "DSTC8-SGD", "HWU64", "MIT-Movie",
+                        "MIT-Restaurant", "RESTAURANTS8K", "SNIPS", "SNIPS-NER", "TOP", "TOP-NER"
+                    ],    
+    "task_oriented": [
+                        "ABCD", "AirDialogue", "BiTOD", "CaSiNo", "CraigslistBargains", 
+                        "Disambiguation", "DSTC2-Clean", "FRAMES", "GECOR", "HDSA-Dialog", 
+                        "KETOD", "KVRET", "MetaLWOZ", "MS-DC", "MuDoCo", 
+                        "MulDoGO", "MultiWOZ_2.1", "MULTIWOZ2_2", "SGD", "SimJointGEN", 
+                        "SimJointMovie", "SimJointRestaurant", "STAR", "Taskmaster1", "Taskmaster2", 
+                        "Taskmaster3", "WOZ2_0"
+                    ],
+    "conversational_recommendation": [
+                        "Redial", "DuRecDial-2.0", "OpenDialKG", "SalesBot",
+                    ]
+}
+
+_URL = "https://huggingface.co/datasets/Salesforce/dialogstudio/tree/main/"
+
+class DialogStudioConfig(BuilderConfig):
+    """BuilderConfig for DialogStudio."""
+
+    def __init__(self, extra_features, category, data_name, citation, url, **kwargs):
+        """BuilderConfig for DialogStudio.
+        Args:
+          extra_features: `list[string]`, list of the features that will appear in the
+            feature dict. Should not include "label".
+          data_url: `string`, url to download the zip file from.
+          citation: `string`, citation for the data set.
+          url: `string`, url for information about the data set.
+          label_classes: `list[string]`, the list of classes for the label if the
+            label is present as a string. Non-string labels will be cast to either
+            'False' or 'True'.
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(DialogStudioConfig, self).__init__(version=_VERSION, **kwargs)
+        self.extra_features = extra_features
+        self.category = category
+        self.data_name = data_name
+        self.compressed_file = f"{data_name}.zip"
+        self.citation = citation
+        self.url = url
+
+
+class DialogStudio(GeneratorBasedBuilder):
+    """DialogStudio"""
+    BUILDER_CONFIGS = []
+    for category, dataset_list in DATASETS.items():
+        if category in ["task_oriented", "conversational_recommendation"]:
+            extra_features = {
+                    "dialog":[
+                            "external knowledge non-flat",
+                            "external knowledge", 
+                            "dst knowledge",
+                            "intent knowledge",
+                        ], 
+                    "turn":[
+                            "dst",
+                            "dst accumulated",
+                            "intent",
+                            "external knowledge", 
+                            "external knowledge non-flat"
+                        ]
+                    }
+        elif category in ["natural_language_understanding"]:
+            extra_features = {"dialog":[], "turn":["external knowledge", "external knowledge non-flat"]}
+        else:
+            extra_features = {"dialog":[], "turn":[]}
+
+        for data_name in dataset_list:
+            BUILDER_CONFIGS.append(
+                DialogStudioConfig(
+                    name=data_name,
+                    data_name=data_name,
+                    description="",
+                    extra_features=extra_features,
+                    category=category,
+                    citation=_CITATION,
+                    url="https://github.com/salesforce/DialogStudio/tree/main",
+            ))
+    
+    DEFAULT_CONFIG_NAME = "WOZ2_0"
+
+    def _info(self):
+        features = {
+                    "original dialog id": Value("string"),
+                    "new dialog id": Value("string"),
+                    "dialog index": Value("int32"),
+                    "original dialog info": Value("string"),
+                    "log": [
+                        {
+                            "turn id": Value("int32"),
+                            "user utterance": Value("string"),
+                            "system response": Value("string"),
+                            "dialog history": Value("string"),
+                            "original user side information": Value("string"),
+                            "original system side information": Value("string"),
+                        }
+                    ],
+                    "prompt": [Value("string")]
+                }
+        if self.config.extra_features["dialog"]:
+            for name in self.config.extra_features["dialog"]:
+                features[name] = Value("string")
+        if self.config.extra_features["turn"]:
+            log_config = {
+                            "turn id": Value("int32"),
+                            "user utterance": Value("string"),
+                            "system response": Value("string"),
+                            "dialog history": Value("string"),
+                            "original user side information": Value("string"),
+                            "original system side information": Value("string"),
+                        }
+            for name in self.config.extra_features["turn"]:
+                log_config[name] = Value("string")
+            features["log"] = [log_config]
+        
+        return DatasetInfo(
+            description="",
+            features=Features(features),
+            homepage=self.config.url,
+            citation=_CITATION,
+        )
+
+    
+    def _split_generators(self, dl_manager):
+        """
+        This script assume the datset is not stored in zip file
+        Instead, data is stored in format:
+        .
+         |-task-oriented
+                |-WOZ2.0
+                    |-train
+                        |-dialogues_1.json
+                        |-dialogues_2.json
+                        |-...
+        this script would download the json file one-by-one
+        """
+
+        splits = []
+        file_path_list = {"train":[], "val":[], "test":[]} 
+        print("❤️Attention❤️: Dataset download may take some time. We appreciate your patience!")
+        for mode in ["train", "val", "test"]:
+            for file_idx in range(1, 1000000):
+                file_to_download = os.path.join(self.config.category, self.config.data_name, mode, f"dialogues_{file_idx}.json")
+                try:
+                    dl_path = dl_manager.download(file_to_download)
+                except:
+                    break
+                file_path_list[mode].append(dl_path)
+
+        if file_path_list["train"]:
+            if any(split.name == datasets.Split.TRAIN for split in splits):
+                raise ValueError("Split 'train' already added.")
+            splits.append(
+                SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "file_path_list": file_path_list["train"],
+                        "split": datasets.Split.TRAIN,
+                    },
+                )
+            )
+        if file_path_list["val"]:
+            if any(split.name == datasets.Split.VALIDATION for split in splits):
+                raise ValueError("Split 'validation' already added.")
+            splits.append(
+                SplitGenerator(
+                    name=datasets.Split.VALIDATION,
+                    gen_kwargs={
+                        "file_path_list": file_path_list["val"],
+                        "split": datasets.Split.VALIDATION,
+                    },
+                )
+            )
+        if file_path_list["test"]:
+            if any(split.name == datasets.Split.TEST for split in splits):
+                raise ValueError("Split 'test' already added.")
+            splits.append(
+                SplitGenerator(
+                    name=datasets.Split.TEST,
+                    gen_kwargs={
+                        "file_path_list": file_path_list["test"],
+                        "split": datasets.Split.TEST,
+                    },
+                )
+            )
+        return splits
+
+
+    def _load_json(self, file_path):
+        with open(file_path, encoding="utf-8") as f:
+            data = json.loads(f.read())
+        return data
+
+
+    def _generate_examples(self, file_path_list, split):
+        """This function returns the examples in the raw (text) form."""
+        data = {}
+        for filepath in file_path_list:
+            data.update(self._load_json(filepath))
+        
+        logger.info(f"generating {len(data)} examples from = {split}")
+
+        for dial_id, dial in data.items():
+            if type(dial["log"]) == dict:
+                dial["log"] = [dial["log"]]
+            example = {
+                "original dialog id": dial["original dialog id"],
+                "new dialog id": dial_id,
+                "dialog index": dial["dialog index"],
+                "original dialog info": json.dumps(dial["original dialog info"]),
+                "log": [{
+                        "turn id": turn["turn id"],
+                        "user utterance": turn["user utterance"],
+                        "system response": turn["system response"],
+                        "dialog history": turn["dialog history"],
+                        "original user side information": json.dumps(turn["original user side information"]),
+                        "original system side information": json.dumps(turn["original system side information"]),
+                    } for turn in dial["log"]],
+                "prompt": dial["prompt"] if "prompt" in dial and dial["prompt"] else [""]
+            }
+            if self.config.extra_features["dialog"]:
+                for name in self.config.extra_features["dialog"]:
+                    example[name] = json.dumps(dial[name]) if name in dial else ""
+            if self.config.extra_features["turn"]:
+                for idx, turn in enumerate(example["log"]):
+                    for name in self.config.extra_features["turn"]:
+                        example["log"][idx][name] = json.dumps(dial["log"][idx][name]) if name in dial["log"][idx] else ""
+            yield dial["dialog index"], example
+

dialogue-summarization/AMI/README.md

@@ -0,0 +1,27 @@
+# AMI Corpora
+
+[AMI Corpus Overview](https://groups.inf.ed.ac.uk/ami/corpus/overview.shtml)
+
+A brief introduction to the AMI Meeting Corpus.
+
+This is a web version of the following newsletter article:
+
+Carletta, J. (2006) Announcing the AMI Meeting Corpus. The ELRA Newsletter 11(1), January-March, p. 3-5.
+
+Announcing the AMI Meeting Corpus
+The European-funded AMI project (FP6-506811) is a 15-member multi-disciplinary consortium dedicated to the research and development of technology that will help groups interact better. One AMI focus is on developing meeting browsers that improve work group effectiveness by giving better access to the group's history. Increasingly in future, we will be considering how related technologies can help group members joining a meeting late or having to "attend" from a different location. In both cases, a key part our approach is to index meetings for the properties that users find salient. This might mean, for instance, spotting topic boundaries, decisions, intense discussions, or places where a specific person or subject was mentioned. To help with developing this indexing the consortium has collected the AMI Meeting Corpus, a set of recorded meetings that is now available as a public resource. Although the data set was designed specifically for the project, it could be used for many different purposes in linguistics, organizational and social psychology, speech and language engineering, video processing, and multi-modal systems.
+
+The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals synchronized to a common timeline. These include close-talking and far-field microphones, individual and room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings, the participants also have unsynchronized pens available to them that record what is written. The meetings were recorded in English using three different rooms with different acoustic properties, and include mostly non-native speakers.
+
+
+
+For more details of these annotations, please refer to the [annotation guidelines](https://groups.inf.ed.ac.uk/ami/corpus/guidelines.shtml) or the citations in below.
+
+
+### Citation:
+
+The data is originally from [The AMI meeting corpus](https://d1wqtxts1xzle7.cloudfront.net/50793769/The_AMI_meeting_corpus20161208-17868-1xaka8f-libre.pdf?1481255943=&response-content-disposition=inline%3B+filename%3DThe_AMI_Meeting_Corpus.pdf&Expires=1690239442&Signature=IEM2L-siuuBS6rwhh5C-w7NthOVlZGb0m12CYvrR59d4rECuowhYoW1F~403O3V4L2tJI6gokXgm9n1QBXS-wQfRiNCRv4uVVNZ60-Mbf1hz~rQJpJ4iBTHHhyZTiGyO~VbCWiqJhS5lAC5cGGzsefKjaxqBLnHnF-Mq6M7c6Q7PMFLToRu9K7hAoFNbJTc7GoA72hUUyoQprYJ6f0VaDmRyrVQJYaYQxHvPiZ9-bjH2-NOVpnolVQP5LYT5AYcrpV~FcmzKvBd7cyl5fxD4EsWcAsvMotv0cCnhoCra20uatZAUz9G8ZpID~9lkMWOaOLPxwJruOPoXoBCAA7R5oQ__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA), and the corresponding website is [link](https://groups.inf.ed.ac.uk/ami/corpus/overview.shtml).
+
+We further process the data based on https://github.com/guokan-shang/ami-and-icsi-corpora.
+
+Please cite their work accordingly if you use the dataset. 

dialogue-summarization/AMI/license.md

@@ -0,0 +1,3 @@
+https://groups.inf.ed.ac.uk/ami/
+
+<a rel="license" href="http://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.

dialogue-summarization/CRD3/LICENSE.txt

@@ -0,0 +1,427 @@
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dialogue-summarization/CRD3/README.md

@@ -0,0 +1,142 @@
+# [ACL 2020] Storytelling with Dialogue: A *Critical Role* Dungeons and Dragons Dataset
+
+
+# Overview
+
+This paper describes the Critical Role Dungeons and Dragons Dataset (CRD3) and related analyses. Critical Role is an unscripted, live-streamed show where a fixed group of people play Dungeons and Dragons, an open-ended role-playing game. The dataset is collected from 159 Critical Role episodes transcribed to text dialogues, consisting of 398,682 turns. It also includes corresponding abstractive summaries collected from the Fandom wiki. The dataset is linguistically unique in that the narratives are generated entirely through player collaboration and spoken interaction. For each dialogue, there are a large number of turns, multiple abstractive summaries with varying levels of detail, and semantic ties to the previous dialogues. In addition, we provide a data augmentation method that produces 34,243 summary-dialogue chunk pairs to support current neural ML approaches, and we provide an abstractive summarization benchmark and evaluation.
+
+Here is an example of a summary chunk aligned to a section in the dialogue, as shown in the paper:
+
+<img src="images/figure 1.PNG" width="35%">
+
+Here is a comparison of the dataset to similar datasets, as shown in the paper:
+
+<img src="images/table 1.PNG" width="75%">
+
+## Repo Structure
+    .
+    ├── baseline                  # The baseline folder will feature a frozen set of data and code to reproduce statistics and metrics calculated in the paper
+    │   ├── data                  # Folder structure for data same as below
+    │   │   └── ...
+    │   └── ...
+    ├── data                      # All of the data (including future updates) for the CRD3 Dataset will be available in the data folder
+    │   ├── aligned data          # The final summary-dialogue chunk aligned data
+    │   │   ├── c=2               # Alignments using summary chunk sizes of size 2
+    │   │   ├── c=3               # ...of size 3
+    │   │   ├── c=4               # ...of size 4
+    │   │   ├── c=...n            # ...of size n if more sizes are added
+    │   │   ├── test_files        # Campaign and episode numbers for files belonging to test set (format ex: 'C2E031')
+    │   │   ├── val_files         # Campaign and episode numbers for files belonging to validation set
+    │   │   └── train_files       # Campaign and episode numbers for files belonging to training set
+    │   ├── cleaned data          # The cleaned transcript data and associated episode summary (cleaning described in paper)
+    │   └── raw summary data      # The raw summary data as extracted from the wiki
+    └── ...
+					
+Source files for helping with data exploration and iteration to be added soon!
+
+## .../data/aligned data/ Usage
+
+Each of json files in `.../data/aligned data/c=.../*.json` has the following filename format:
+```
+C<campaign number>E<episode number>_<summary chunk size>_<sentence offset>.json
+```
+Taking `C1E001_2_1.json` as an example: this is the aligned data for campaign 1, episode 1 with chunk size 2, chunks offset by 1.
+The offset is the number of sentences after sentence 1 in the summary that the chunking starts from. For example, with a summary with sentences `[A,B,C,D,E]` a chunk size of 2 and offset of 1 would produce the chunks `[BC,CD,DE]`. Each dialogue and associated summary is chunked using all chunk sizes, thus the entire dialogue summary set is currently available in chunk sizes 2, 3, and 4 as described in the paper.
+
+To see if a json file is in test, val, or train set (as defined in the paper), simply check if  the campaign and episode substring (ex: `C1E001`) are in one of the sets.
+
+The JSON schema for the aligned data is as follows:
+```
+[
+  {
+    "CHUNK": (str) The summary chunk after the chunking process.,
+    "ALIGNMENT": {
+      "CHUNK ID": (int) The chunk position for the specified chunk size and offset,
+      "TURN START": (int) The turn position of the dialogue that the alignment starts at,
+      "TURN END": (int) The turn position of the dialogue that the alignment ends at,
+      "ALIGNMENT SCORE": (float) The alignmed score of the summary chunk pair (details in paper)
+    },
+    "TURNS": [
+      {
+        "NAMES": [
+          (str) List of names associated with that specific turn. If more than name is in list, the transcribers have associated the utterances with all specified names.
+        ],
+        "UTTERANCES": [
+         (str) List of utterances in the turn, they are broken into chunks as specified by the transcribers.
+        ],
+        "NUMBER": (int) Turn position in the dialogue
+      }
+    ]
+  },
+  ...
+]
+```
+Turn numbers for the dialogues start from 0 and go to `len([dialogue turns])-1`.
+
+Example:
+```
+[
+  {
+    "CHUNK": "Matthew Mercer introduces himself and the concept of Critical Role. The introduction videos for Grog, Keyleth, Percy, Scanlan, Tiberius, Vax'ildan, and Vex'ahlia are shown.",
+    "ALIGNMENT": {
+      "CHUNK ID": 0,
+      "TURN START": 0,
+      "TURN END": 0,
+      "ALIGNMENT SCORE": 0
+    },
+    "TURNS": [
+      {
+        "NAMES": [
+          "MATT"
+        ],
+        "UTTERANCES": [
+          "Hello everyone. My name is Matthew Mercer,",
+          "voice actor and Dungeon Master for Critical Role",
+          "on Geek & Sundry, where I take a bunch of other",
+          "voice actors and run them through a fantastical",
+          "fantasy adventure through the world of Dungeons &",
+          "Dragons. We play every Thursday at 7:00pm Pacific",
+          "Standard Time on Geek & Sundry's Twitch stream.",
+          "Please come watch us live if you have the",
+          "opportunity. Back episodes and future episodes",
+          "will be uploaded on the Geek & Sundry website. You",
+          "can also check them out there. In the meantime,",
+          "enjoy!"
+        ],
+        "NUMBER": 0
+      }
+    ]
+  },
+  ...
+]
+```
+
+## Citation
+
+Please cite the following paper if you want to use this dataset in your research
+```
+R. Rameshkumar and P. Bailey. Storytelling with Dialogue: A Critical Role Dungeons and Dragons Dataset. ACL 2020.
+
+@inproceedings{
+    title = "Storytelling with Dialogue: A Critical Role Dungeons and Dragons Dataset",
+    author = "Rameshkumar, Revanth  and
+      Bailey, Peter",
+    year = "2020",
+    publisher = "Association for Computational Linguistics",
+    conference = "ACL"
+}
+```
+
+## Acknowledgements
+
+We thank the [Critical Role](https://critrole.com/team/) team for creating a fun, entertaining, organized,and growing set of livestreams that we used in this dataset. We also thank the [CRTranscript](https://crtranscript.tumblr.com/about) team for providing high quality transcripts of the show for the community and we thank all the contributors of the [Critical Role Wiki](https://criticalrole.fandom.com/).
+
+## Contact and Discuss!
+
+Feel free to reach out to us via this repo with questions or comments!
+
+
+
+
+This work is licensed under a [Creative Commons Attribution-ShareAlike 4.0
+International License][cc-by-sa]., as corresponding to the Critical Role Wiki https://criticalrole.fandom.com/

dialogue-summarization/ConvoSumm/LICENSE

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dialogue-summarization/ConvoSumm/README.md

@@ -0,0 +1,28 @@
+# ConvoSumm
+Data, code, and model checkpoints for the ACL 2021 paper [ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument Mining](https://arxiv.org/pdf/2106.00829.pdf)!
+</br>
+
+## Data
+The data can be accessed from this [Google Drive link](https://drive.google.com/drive/folders/1HfyCMa1fQ5DkzME9RQZkytZQfyDjE1EK?usp=sharing). </br>
+
+The `data-non-processed` contains the original, non-processed data and is 27MB, while `data-processed` contains the data for vanilla, **-arg-filtered**, and **-arg-graph** experiments, as well as model outputs, and is 611 MB. </br>
+
+Using the [gdrive cli](https://github.com/prasmussen/gdrive), download the folders with the following command </br>
+```
+gdrive download --recursive 1HfyCMa1fQ5DkzME9RQZkytZQfyDjE1EK
+```
+
+The data can also be downloaded from this [S3 bucket](https://s3.console.aws.amazon.com/s3/buckets/convosumm). </br>
+```
+aws s3 cp --recursive s3://convosumm/data/ ./data
+```
+
+
+## Code and Model Checkpoints
+Please see this [README](https://github.com/Yale-LILY/ConvoSumm/blob/master/code/README.md) for code details. </br>
+
+Model checkpoints can be downloaded from the S3 bucket (~80GB): </br> 
+```
+aws s3 cp --recursive s3://convosumm/checkpoints/ ./checkpoints
+```
+

dialogue-summarization/ConvoSumm/converted_examples.json

@@ -0,0 +1,52 @@
+{
+    "ConvoSumm--train--1": {
+        "original dialog id": "",
+        "dialog index": 1,
+        "original dialog info": {
+            "summary": "Commenters respond to a question placed by the Original POster as to what time the AMD presentation starts there in the Netherlands. Most responses answer back with the time frame converted to 12 PM EST. another comment states that it takes place at the same time as the Nintendo E3 Conference.",
+            "dialog history": "Title: Does anybody know at what time the AMD presentation will be for the netherlands? Subreddit: pcmasterrace I'm really bad with timezones. Its in 3 hours and 4 minutes. its at 8pm ET, its now 9am ET Their official twitch states 9am pst 12pm est. is there a seperate amd show besides the pc gaming one? I dont believe I have no clue where you got 8 from since i went to their twitter and all the post are about the one at 12 today. its the same time as nintendos E3 confernece , so in abput 3/4 hours It starts at 2 AM for you, I believe. 1800 for central and 1900 for eastern europe",
+            "sub dataset": "reddit"
+        },
+        "log": ""
+    },
+    "ConvoSumm--train--2": {
+        "original dialog id": "",
+        "dialog index": 2,
+        "original dialog info": {
+            "summary": "Some commenters do not recommend using oil at all, while others like using it. Those who use oil differ in their opinions about which oils to use, such as Safflower or Coconut oil, but do not suggest using olive oil or vegetable oil. Those who do not use oil suggest using nothing or preparing the pan with water instead of the oil.",
+            "dialog history": "Title: Best oil to cook with for losing weight Subreddit: diet Title says it all, I was wondering what the best oil to cook stuff in a ban is. like say stir frying veggies or scrambling egg whites. I'm sure there was more calories in the oil I used this morning than the eggs I ate haha I think all oils, aka fat have very similar caloric value Coconut oil. The other oils are bad for you and olive oil does bad things when heated. I agree coconut oil or MCT oil is the best for you with no noticeable added taste I use it for cooking everything. You can even use it as lip balm or for treating dry skin and dandruff a was watching the hairy bikers diet show thing and they dry fry everything and ive started doing that. Things taste better. No oil. Just put your food in. start on a low heat and get higher Wait, wouldn't that make food stick? Not if you cook it on low first like really low then once the fats started to come out of it then crank it up a little more. and it cooks in its own oil then and doesnt stick. Also, Teflon is legit. Even the crummy $10 pan I got at walmart keeps things from sticking at all. I usually always go with olive oil and sometimes safflower oil for the health benefits for women. Avoid vegetable oil at all costs. These are polyunsaturates that cause so many health problems because they tend to become oxidized or rancid when subjected to heat, oxygen and moisture as in cooking and processing. Go for coconut and olive oil. Coconut oil is heat stable, will give you more energy and help you lose weight. It is a medium-chain fat. water, in a spritz bottle.",
+            "sub dataset": "reddit"
+        },
+        "log": ""
+    },
+    "ConvoSumm--train--3": {
+        "original dialog id": "",
+        "dialog index": 3,
+        "original dialog info": {
+            "summary": "Commentators agree that the location does not have valet parking. Two commentators advise going to a nearby garage that\u2019s a few blocks away. One commentator gives a rude reply, which leads another commentator to try and offer sympathy. His efforts are rudely rebuffed.",
+            "dialog history": "Title: Does Kimmel Center have valet parking? Subreddit: philadelphia I was reading about parking on their website but there is no indication. The website only points to their parking garage where you have to make reservations. No valet parking, but if you drive up Spruce to 15th, there's a very good garage above Fox and Hound. If you really don't wanna park on your own, you can drive over to the hotels on 17th. Thank you for the helpful information Get to that garage early and have a backup garage. It fills up early every time there's an event. You know what companies who have valet parking do? They advertise that they have valet parking. do you need a hug? I'm perfectly contented just watching you work so hard trying to stuff that straw man. Do you need a diaper change or something? That's usually mom's job It takes a village. ps I've been to plenty of places that don't indicate valet when they do have it. I've also seen places that advertise it but it's not available at certain times, or it's for a different price than advertised, or it's with a 3rd party company, etc. That was why I asked for clarification.",
+            "sub dataset": "reddit"
+        },
+        "log": ""
+    },
+    "ConvoSumm--train--4": {
+        "original dialog id": "",
+        "dialog index": 4,
+        "original dialog info": {
+            "summary": "Commenters offer their movie(s) that they can practically quote word for one. One mentions Dumb and Dumber, and another said Shutter Island, which one mentions is good. Another mentions Predator or Aliens. Overall, there are various movies mentioned with very little similarity.",
+            "dialog history": "Title: what movie(s) have you seen so many times you can practically quote it word for word? Subreddit: movies for me its Mean Girls. I spent one summer, with my best friend, watching it at least once a week. * Pulp Fiction * Wayne's World Mrs Doubtfire One time we watched it at his now-ex gf's house and for some reason the sound wouldn't work. We watched it anyway and made the dialogue up ourselves, full of swearing and Street Fighter moves) Knocked Up. I was going through a rough time when it came out and saw it like 8 times in the theatre. I saw that in theaters! very funny movie. ferris bueller's day off and christmas vacation are two big ones. probably the first two dark knight movies. probably the lost boys. big trouble in little china. The Big Lebowski. Coen Brothers movies are infinitely rewatchable. Pilgrim vs. the World Madison -Happy I have most of Scott pilgrim memorized too! my boyfriend (at the time) and I saw it 3 times in theaters. *Forrest Gump* Napoleon Dynamite and Just Friends The Matrix Ferris Bueller's Day Off and Blues Brothers Princess Bride or Blues Brothers Forrest Gump, The Mask, Toy Story, Aladdin, The Lion King - all the movies I grew up watching. Disney movies are the best! Monty python and the holy grail Blue brothers Atonement, Big Fish, Shutter Island, Pride and Prejudice oooo shutter island is a good one. Wanna Wrestle? Sideways & Office Space Very many movies, but mainly my favorite movie of all time, Predator. Tremors Fargo. Me and a co-worker of mine quote (re-enact) pretty much every scene, Favorite movie of all time. Aliens, my dad let me watch it with him when i was young (probably too young) and he could never again watch it with me i would always quote the lines before they were said. Talladega nights: the ballad of Ricky bobby Animal House, Minority Report, and Kung Fu Hustle. The Count of Monte Cristo. I wore out the VHS. That's how much I love this movie. Richard Harris' Abb\u00e9 Faria is one of my favourite movie characters ever. I'm a priest, not a saint. Gives me chills every time. spongebob squarepants movie! Blazing Saddles",
+            "sub dataset": "reddit"
+        },
+        "log": ""
+    },
+    "ConvoSumm--train--5": {
+        "original dialog id": "",
+        "dialog index": 5,
+        "original dialog info": {
+            "summary": "The commenters respond to a post about a new, up and coming adult entertainment center providing bowling, billiards, video arcade games, and laser tag along with a bar and restaurant. The facility is advertising unlimited laser tag and bowling for a straight fee of $25.00 on a particular day. One of the commentators is curious about whether it is worth it.  Some commenters enjoy the facility's array of entertainment options.  Other commenters say that they had never heard of the place before, having lived in the area most of their lives.",
+            "dialog history": "Title: Unlimited laser tag and bowling on Memorial Day! Subreddit: batonrouge We are having unlimited laser tag and bowling here at Quarters for $25 on Monday, May 26th! All you have do is be wearing a visible article of clothing colored red, white, or blue! Quarters: bringing Baton Rouge's gangs together for laser tag. I'd rather hear about Baton Rougeans shooting each other with lasers than with lead. My question for every other member of this subreddit: Is bowling and laser tag any good at quarters? I've heard mixed reviews about the place and don't feel like dumping $25 to find out for myself. The bowling is great, the laser tag is good. They have comfy leather seats in the bowling area, which is right across from the bar (you can order food at the bar as well). I don't really like playing laser tag so I'm not the best judge on it. What and where is Quarters? I've lived in Baton Rouge my whole life and have never heard of this place. It's pretty new. In the same shopping center as lil Caesars on the corner of Sherwood and coursey. We're at the corner of Sherwood and Coursey in the Lake Sherwood Mall Shopping Center. We're a relatively new and up and coming adult entertainment center. You need a better selection of video games and lower prices to play them. We're currently getting a lot of new video games in and the prices are pretty normal for an arcade in Baton Rouge. What is Quarters and why have I never heard of it? A lot of people haven't heard of us, we're pretty new to the game. We are a bar, restaurant, bowling, billards, arcade, and laser tag facility.",
+            "sub dataset": "reddit"
+        },
+        "log": ""
+    }
+}

dialogue-summarization/ConvoSumm/original_examples.json

@@ -0,0 +1,27 @@
+[
+    {
+        "dialog history": "Title: Does anybody know at what time the AMD presentation will be for the netherlands? Subreddit: pcmasterrace I'm really bad with timezones. Its in 3 hours and 4 minutes. its at 8pm ET, its now 9am ET Their official twitch states 9am pst 12pm est. is there a seperate amd show besides the pc gaming one? I dont believe I have no clue where you got 8 from since i went to their twitter and all the post are about the one at 12 today. its the same time as nintendos E3 confernece , so in abput 3/4 hours It starts at 2 AM for you, I believe. 1800 for central and 1900 for eastern europe\n",
+        "summary": "Commenters respond to a question placed by the Original POster as to what time the AMD presentation starts there in the Netherlands. Most responses answer back with the time frame converted to 12 PM EST. another comment states that it takes place at the same time as the Nintendo E3 Conference.\n",
+        "sub dataset": "reddit"
+    },
+    {
+        "dialog history": "Title: Best oil to cook with for losing weight Subreddit: diet Title says it all, I was wondering what the best oil to cook stuff in a ban is. like say stir frying veggies or scrambling egg whites. I'm sure there was more calories in the oil I used this morning than the eggs I ate haha I think all oils, aka \"fat\" have very similar caloric value Coconut oil. The other oils are bad for you and olive oil does bad things when heated. I agree coconut oil or MCT oil is the best for you with no noticeable added taste I use it for cooking everything. You can even use it as lip balm or for treating dry skin and dandruff a was watching the hairy bikers diet show thing and they dry fry everything and ive started doing that. Things taste better. No oil. Just put your food in. start on a low heat and get higher Wait, wouldn't that make food stick? Not if you cook it on low first like really low then once the fats started to come out of it then crank it up a little more. and it cooks in its own oil then and doesnt stick. Also, Teflon is legit. Even the crummy $10 pan I got at walmart keeps things from sticking at all. I usually always go with olive oil and sometimes safflower oil for the health benefits for women. Avoid vegetable oil at all costs. These are polyunsaturates that cause so many health problems because they tend to become oxidized or rancid when subjected to heat, oxygen and moisture as in cooking and processing. Go for coconut and olive oil. Coconut oil is heat stable, will give you more energy and help you lose weight. It is a medium-chain fat. water, in a spritz bottle.\n",
+        "summary": "Some commenters do not recommend using oil at all, while others like using it. Those who use oil differ in their opinions about which oils to use, such as Safflower or Coconut oil, but do not suggest using olive oil or vegetable oil. Those who do not use oil suggest using nothing or preparing the pan with water instead of the oil.\n",
+        "sub dataset": "reddit"
+    },
+    {
+        "dialog history": "Title: Does Kimmel Center have valet parking? Subreddit: philadelphia I was reading about parking on their website but there is no indication. The website only points to their parking garage where you have to make reservations. No valet parking, but if you drive up Spruce to 15th, there's a very good garage above Fox and Hound. If you really don't wanna park on your own, you can drive over to the hotels on 17th. Thank you for the helpful information Get to that garage early and have a backup garage. It fills up early every time there's an event. You know what companies who have valet parking do? They advertise that they have valet parking. do you need a hug? I'm perfectly contented just watching you work so hard trying to stuff that straw man. Do you need a diaper change or something? That's usually mom's job It takes a village. ps I've been to plenty of places that don't indicate valet when they do have it. I've also seen places that advertise it but it's not available at certain times, or it's for a different price than advertised, or it's with a 3rd party company, etc. That was why I asked for clarification.\n",
+        "summary": "Commentators agree that the location does not have valet parking. Two commentators advise going to a nearby garage that\u2019s a few blocks away. One commentator gives a rude reply, which leads another commentator to try and offer sympathy. His efforts are rudely rebuffed.\n",
+        "sub dataset": "reddit"
+    },
+    {
+        "dialog history": "Title: what movie(s) have you seen so many times you can practically quote it word for word? Subreddit: movies for me its Mean Girls. I spent one summer, with my best friend, watching it at least once a week. * Pulp Fiction * Wayne's World Mrs Doubtfire One time we watched it at his now-ex gf's house and for some reason the sound wouldn't work. We watched it anyway and made the dialogue up ourselves, full of swearing and Street Fighter moves) Knocked Up. I was going through a rough time when it came out and saw it like 8 times in the theatre. I saw that in theaters! very funny movie. ferris bueller's day off and christmas vacation are two big ones. probably the first two dark knight movies. probably the lost boys. big trouble in little china. The Big Lebowski. Coen Brothers movies are infinitely rewatchable. Pilgrim vs. the World Madison -Happy I have most of Scott pilgrim memorized too! my boyfriend (at the time) and I saw it 3 times in theaters. *Forrest Gump* Napoleon Dynamite and Just Friends The Matrix Ferris Bueller's Day Off and Blues Brothers Princess Bride or Blues Brothers Forrest Gump, The Mask, Toy Story, Aladdin, The Lion King - all the movies I grew up watching. Disney movies are the best! Monty python and the holy grail Blue brothers Atonement, Big Fish, Shutter Island, Pride and Prejudice oooo shutter island is a good one. Wanna Wrestle? Sideways & Office Space Very many movies, but mainly my favorite movie of all time, Predator. Tremors Fargo. Me and a co-worker of mine quote (re-enact) pretty much every scene, Favorite movie of all time. Aliens, my dad let me watch it with him when i was young (probably too young) and he could never again watch it with me i would always quote the lines before they were said. Talladega nights: the ballad of Ricky bobby Animal House, Minority Report, and Kung Fu Hustle. The Count of Monte Cristo. I wore out the VHS. That's how much I love this movie. Richard Harris' Abb\u00e9 Faria is one of my favourite movie characters ever. \"I'm a priest, not a saint.\" Gives me chills every time. spongebob squarepants movie! Blazing Saddles\n",
+        "summary": "Commenters offer their movie(s) that they can practically quote word for one. One mentions Dumb and Dumber, and another said Shutter Island, which one mentions is good. Another mentions Predator or Aliens. Overall, there are various movies mentioned with very little similarity.\n",
+        "sub dataset": "reddit"
+    },
+    {
+        "dialog history": "Title: Unlimited laser tag and bowling on Memorial Day! Subreddit: batonrouge We are having unlimited laser tag and bowling here at Quarters for $25 on Monday, May 26th! All you have do is be wearing a visible article of clothing colored red, white, or blue! Quarters: bringing Baton Rouge's gangs together for laser tag. I'd rather hear about Baton Rougeans shooting each other with lasers than with lead. My question for every other member of this subreddit: Is bowling and laser tag any good at quarters? I've heard mixed reviews about the place and don't feel like dumping $25 to find out for myself. The bowling is great, the laser tag is good. They have comfy leather seats in the bowling area, which is right across from the bar (you can order food at the bar as well). I don't really like playing laser tag so I'm not the best judge on it. What and where is Quarters? I've lived in Baton Rouge my whole life and have never heard of this place. It's pretty new. In the same shopping center as lil Caesars on the corner of Sherwood and coursey. We're at the corner of Sherwood and Coursey in the Lake Sherwood Mall Shopping Center. We're a relatively new and up and coming adult entertainment center. You need a better selection of video games and lower prices to play them. We're currently getting a lot of new video games in and the prices are pretty normal for an arcade in Baton Rouge. What is Quarters and why have I never heard of it? A lot of people haven't heard of us, we're pretty new to the game. We are a bar, restaurant, bowling, billards, arcade, and laser tag facility.\n",
+        "summary": "The commenters respond to a post about a new, up and coming adult entertainment center providing bowling, billiards, video arcade games, and laser tag along with a bar and restaurant. The facility is advertising unlimited laser tag and bowling for a straight fee of $25.00 on a particular day. One of the commentators is curious about whether it is worth it.  Some commenters enjoy the facility's array of entertainment options.  Other commenters say that they had never heard of the place before, having lived in the area most of their lives.\n",
+        "sub dataset": "reddit"
+    }
+]

dialogue-summarization/DialogSum/LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2021 Yulong Chen
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

dialogue-summarization/DialogSum/README.md

@@ -0,0 +1,63 @@
+# DialogSum: A Real-life Scenario Dialogue Summarization Dataset
+
+DialogSum is a large-scale dialogue summarization dataset, consisting of 13,460 dialogues with corresponding manually labeled summaries and topics.
+You can directly download the data from this [fold](https://github.com/cylnlp/dialogsum/tree/main/DialogSum_Data), or from the Hugging face [Dataset](https://huggingface.co/datasets/knkarthick/dialogsum).
+
+This work is accepted by ACL findings 2021. You may find the paper [here](https://aclanthology.org/2021.findings-acl.449).
+If you use our dataset, please kindly cite our paper:
+```
+@inproceedings{chen-etal-2021-dialogsum,
+    title = "{D}ialog{S}um: {A} Real-Life Scenario Dialogue Summarization Dataset",
+    author = "Chen, Yulong  and
+      Liu, Yang  and
+      Chen, Liang  and
+      Zhang, Yue",
+    booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
+    month = aug,
+    year = "2021",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2021.findings-acl.449",
+    doi = "10.18653/v1/2021.findings-acl.449",
+    pages = "5062--5074",
+}
+```
+
+[DialogSum Challenge](https://aclanthology.org/2021.inlg-1.33.pdf) is a shared task at [INLG 2022](https://inlgmeeting.github.io/index.html). Check the [task website](https://cylnlp.github.io/dialogsum-challenge/) and [shared task report](https://arxiv.org/pdf/2208.03898.pdf).
+
+## Quick Start
+We provide a BART baseline for dialogue summarization, which may help you explore this area as a quick start.
+See [Baseline](https://github.com/cylnlp/dialogsum/tree/main/Baseline).
+
+## Dialogue Data
+We collect dialogue data for DialogSum from three public dialogue corpora, namely Dailydialog (Li et al., 2017), DREAM (Sun et al., 2019) and MuTual (Cui et al., 2019), as well as an English speaking practice website. 
+These datasets contain face-to-face spoken dialogues that cover a wide range of daily-life topics, including schooling, work, medication, shopping, leisure, travel.
+Most conversations take place between friends, colleagues, and between service providers and customers.
+
+Compared with previous datasets, dialogues from DialogSum have distinct characteristics: 
+* Under rich real-life scenarios, including more diverse task-oriented scenarios;
+* Have clear communication patterns and intents, which is valuable to serve as summarization sources;
+* Have a reasonable length, which comforts the purpose of automatic summarization.
+
+## Summaries
+We ask annotators to summarize each dialogue based on the following criteria:
+* Convey the most salient information;
+* Be brief;
+* Preserve important named entities within the conversation;
+* Be written from an observer perspective;
+* Be written in formal language.
+
+## Topics
+In addition to summaries, we also ask annotators to write a short topic for each dialogue, which can be potentially useful for future work, e.g. generating summaries by leveraging topic information.
+
+
+
+
+## Reference
+
+* Leyang Cui, Yu Wu, Shujie Liu, Yue Zhang, and Ming Zhou. 2020. MuTual: A dataset for multi-turn dialogue reasoning. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 1406–1416, Online. Association for Computational Linguistics.
+
+* Yanran Li, Hui Su, Xiaoyu Shen, Wenjie Li, Ziqiang Cao, and Shuzi Niu. 2017. DailyDialog: A manually labelled multi-turn dialogue dataset. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 986–995, Taipei, Taiwan. Asian Federation of Natural Language Processing.
+
+* Kai Sun, Dian Yu, Jianshu Chen, Dong Yu, Yejin Choi,and Claire Cardie. 2019. DREAM: A challenge dataset and models for dialogue-based reading comprehension. Transactions of the Association for Computational Linguistics, 7:217–231.
+

dialogue-summarization/DialogSum/converted_examples.json

@@ -0,0 +1,316 @@
+{
+    "DialogSum--train--1": {
+        "original dialog id": "train_0",
+        "dialog index": 1,
+        "original dialog info": {
+            "summary": "Mr. Smith's getting a check-up, and Doctor Hawkins advises him to have one every year. Hawkins'll give some information about their classes and medications to help Mr. Smith quit smoking.",
+            "topic": "get a check-up"
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Hi, Mr. Smith. I'm Doctor Hawkins. Why are you here today?",
+                "system response": "I found it would be a good idea to get a check-up.",
+                "dialog history": "",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 2,
+                "user utterance": "Yes, well, you haven't had one for 5 years. You should have one every year.",
+                "system response": "I know. I figure as long as there is nothing wrong, why go see the doctor?",
+                "dialog history": "<USER> Hi, Mr. Smith. I'm Doctor Hawkins. Why are you here today? <SYSTEM> I found it would be a good idea to get a check-up.",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 3,
+                "user utterance": "Well, the best way to avoid serious illnesses is to find out about them early. So try to come at least once a year for your own good.",
+                "system response": "Ok.",
+                "dialog history": "<USER> Hi, Mr. Smith. I'm Doctor Hawkins. Why are you here today? <SYSTEM> I found it would be a good idea to get a check-up. <USER> Yes, well, you haven't had one for 5 years. You should have one every year. <SYSTEM> I know. I figure as long as there is nothing wrong, why go see the doctor?",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 4,
+                "user utterance": "Let me see here. Your eyes and ears look fine. Take a deep breath, please. Do you smoke, Mr. Smith?",
+                "system response": "Yes.",
+                "dialog history": "<USER> Hi, Mr. Smith. I'm Doctor Hawkins. Why are you here today? <SYSTEM> I found it would be a good idea to get a check-up. <USER> Yes, well, you haven't had one for 5 years. You should have one every year. <SYSTEM> I know. I figure as long as there is nothing wrong, why go see the doctor? <USER> Well, the best way to avoid serious illnesses is to find out about them early. So try to come at least once a year for your own good. <SYSTEM> Ok.",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 5,
+                "user utterance": "Smoking is the leading cause of lung cancer and heart disease, you know. You really should quit.",
+                "system response": "I've tried hundreds of times, but I just can't seem to kick the habit.",
+                "dialog history": "<USER> Hi, Mr. Smith. I'm Doctor Hawkins. Why are you here today? <SYSTEM> I found it would be a good idea to get a check-up. <USER> Yes, well, you haven't had one for 5 years. You should have one every year. <SYSTEM> I know. I figure as long as there is nothing wrong, why go see the doctor? <USER> Well, the best way to avoid serious illnesses is to find out about them early. So try to come at least once a year for your own good. <SYSTEM> Ok. <USER> Let me see here. Your eyes and ears look fine. Take a deep breath, please. Do you smoke, Mr. Smith? <SYSTEM> Yes.",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 6,
+                "user utterance": "Well, we have classes and some medications that might help. I'll give you more information before you leave.",
+                "system response": "Ok, thanks doctor.",
+                "dialog history": "<USER> Hi, Mr. Smith. I'm Doctor Hawkins. Why are you here today? <SYSTEM> I found it would be a good idea to get a check-up. <USER> Yes, well, you haven't had one for 5 years. You should have one every year. <SYSTEM> I know. I figure as long as there is nothing wrong, why go see the doctor? <USER> Well, the best way to avoid serious illnesses is to find out about them early. So try to come at least once a year for your own good. <SYSTEM> Ok. <USER> Let me see here. Your eyes and ears look fine. Take a deep breath, please. Do you smoke, Mr. Smith? <SYSTEM> Yes. <USER> Smoking is the leading cause of lung cancer and heart disease, you know. You really should quit. <SYSTEM> I've tried hundreds of times, but I just can't seem to kick the habit.",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            }
+        ]
+    },
+    "DialogSum--train--2": {
+        "original dialog id": "train_1",
+        "dialog index": 2,
+        "original dialog info": {
+            "summary": "Mrs Parker takes Ricky for his vaccines. Dr. Peters checks the record and then gives Ricky a vaccine.",
+            "topic": "vaccines"
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Hello Mrs. Parker, how have you been?",
+                "system response": "Hello Dr. Peters. Just fine thank you. Ricky and I are here for his vaccines.",
+                "dialog history": "",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 2,
+                "user utterance": "Very well. Let's see, according to his vaccination record, Ricky has received his Polio, Tetanus and Hepatitis B shots. He is 14 months old, so he is due for Hepatitis A, Chickenpox and Measles shots.",
+                "system response": "What about Rubella and Mumps?",
+                "dialog history": "<USER> Hello Mrs. Parker, how have you been? <SYSTEM> Hello Dr. Peters. Just fine thank you. Ricky and I are here for his vaccines.",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 3,
+                "user utterance": "Well, I can only give him these for now, and after a couple of weeks I can administer the rest.",
+                "system response": "OK, great. Doctor, I think I also may need a Tetanus booster. Last time I got it was maybe fifteen years ago!",
+                "dialog history": "<USER> Hello Mrs. Parker, how have you been? <SYSTEM> Hello Dr. Peters. Just fine thank you. Ricky and I are here for his vaccines. <USER> Very well. Let's see, according to his vaccination record, Ricky has received his Polio, Tetanus and Hepatitis B shots. He is 14 months old, so he is due for Hepatitis A, Chickenpox and Measles shots. <SYSTEM> What about Rubella and Mumps?",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            }
+        ]
+    },
+    "DialogSum--train--3": {
+        "original dialog id": "train_2",
+        "dialog index": 3,
+        "original dialog info": {
+            "summary": "#Person1#'s looking for a set of keys and asks for #Person2#'s help to find them.",
+            "topic": "find keys"
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Excuse me, did you see a set of keys?",
+                "system response": "What kind of keys?",
+                "dialog history": "",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 2,
+                "user utterance": "Five keys and a small foot ornament.",
+                "system response": "What a shame! I didn't see them.",
+                "dialog history": "<USER> Excuse me, did you see a set of keys? <SYSTEM> What kind of keys?",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 3,
+                "user utterance": "Well, can you help me look for it? That's my first time here.",
+                "system response": "Sure. It's my pleasure. I'd like to help you look for the missing keys.",
+                "dialog history": "<USER> Excuse me, did you see a set of keys? <SYSTEM> What kind of keys? <USER> Five keys and a small foot ornament. <SYSTEM> What a shame! I didn't see them.",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 4,
+                "user utterance": "It's very kind of you.",
+                "system response": "It's not a big deal.Hey, I found them.",
+                "dialog history": "<USER> Excuse me, did you see a set of keys? <SYSTEM> What kind of keys? <USER> Five keys and a small foot ornament. <SYSTEM> What a shame! I didn't see them. <USER> Well, can you help me look for it? That's my first time here. <SYSTEM> Sure. It's my pleasure. I'd like to help you look for the missing keys.",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 5,
+                "user utterance": "Oh, thank God! I don't know how to thank you, guys.",
+                "system response": "You're welcome.",
+                "dialog history": "<USER> Excuse me, did you see a set of keys? <SYSTEM> What kind of keys? <USER> Five keys and a small foot ornament. <SYSTEM> What a shame! I didn't see them. <USER> Well, can you help me look for it? That's my first time here. <SYSTEM> Sure. It's my pleasure. I'd like to help you look for the missing keys. <USER> It's very kind of you. <SYSTEM> It's not a big deal.Hey, I found them.",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            }
+        ]
+    },
+    "DialogSum--train--4": {
+        "original dialog id": "train_3",
+        "dialog index": 4,
+        "original dialog info": {
+            "summary": "#Person1#'s angry because #Person2# didn't tell #Person1# that #Person2# had a girlfriend and would marry her.",
+            "topic": "have a girlfriend"
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Why didn't you tell me you had a girlfriend?",
+                "system response": "Sorry, I thought you knew.",
+                "dialog history": "",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 2,
+                "user utterance": "But you should tell me you were in love with her.",
+                "system response": "Didn't I?",
+                "dialog history": "<USER> Why didn't you tell me you had a girlfriend? <SYSTEM> Sorry, I thought you knew.",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 3,
+                "user utterance": "You know you didn't.",
+                "system response": "Well, I am telling you now.",
+                "dialog history": "<USER> Why didn't you tell me you had a girlfriend? <SYSTEM> Sorry, I thought you knew. <USER> But you should tell me you were in love with her. <SYSTEM> Didn't I?",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 4,
+                "user utterance": "Yes, but you might have told me before.",
+                "system response": "I didn't think you would be interested.",
+                "dialog history": "<USER> Why didn't you tell me you had a girlfriend? <SYSTEM> Sorry, I thought you knew. <USER> But you should tell me you were in love with her. <SYSTEM> Didn't I? <USER> You know you didn't. <SYSTEM> Well, I am telling you now.",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 5,
+                "user utterance": "You can't be serious. How dare you not tell me you are going to marry her?",
+                "system response": "Sorry, I didn't think it mattered.",
+                "dialog history": "<USER> Why didn't you tell me you had a girlfriend? <SYSTEM> Sorry, I thought you knew. <USER> But you should tell me you were in love with her. <SYSTEM> Didn't I? <USER> You know you didn't. <SYSTEM> Well, I am telling you now. <USER> Yes, but you might have told me before. <SYSTEM> I didn't think you would be interested.",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            }
+        ]
+    },
+    "DialogSum--train--5": {
+        "original dialog id": "train_4",
+        "dialog index": 5,
+        "original dialog info": {
+            "summary": "Malik invites Nikki to dance. Nikki agrees if Malik doesn't mind getting his feet stepped on.",
+            "topic": "dance"
+        },
+        "log": [
+            {
+                "turn id": 1,
+                "user utterance": "Watsup, ladies! Y'll looking'fine tonight. May I have this dance?",
+                "system response": "He's cute! He looks like Tiger Woods! But, I can't dance. . .",
+                "dialog history": "",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 2,
+                "user utterance": "It's all good. I'll show you all the right moves. My name's Malik.",
+                "system response": "Nice to meet you. I'm Wen, and this is Nikki.",
+                "dialog history": "<USER> Watsup, ladies! Y'll looking'fine tonight. May I have this dance? <SYSTEM> He's cute! He looks like Tiger Woods! But, I can't dance. . .",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            },
+            {
+                "turn id": 3,
+                "user utterance": "How you feeling', vista? Mind if I take your friend'round the dance floor?",
+                "system response": "She doesn't mind if you don't mind getting your feet stepped on.",
+                "dialog history": "<USER> Watsup, ladies! Y'll looking'fine tonight. May I have this dance? <SYSTEM> He's cute! He looks like Tiger Woods! But, I can't dance. . . <USER> It's all good. I'll show you all the right moves. My name's Malik. <SYSTEM> Nice to meet you. I'm Wen, and this is Nikki.",
+                "original user side information": {
+                    "speaker": "Person1"
+                },
+                "original system side information": {
+                    "speaker": "Person2"
+                }
+            }
+        ]
+    }
+}

dialogue-summarization/DialogSum/original_examples.json

@@ -0,0 +1,32 @@
+[
+    {
+        "fname": "train_0",
+        "dialogue": "#Person1#: Hi, Mr. Smith. I'm Doctor Hawkins. Why are you here today?\n#Person2#: I found it would be a good idea to get a check-up.\n#Person1#: Yes, well, you haven't had one for 5 years. You should have one every year.\n#Person2#: I know. I figure as long as there is nothing wrong, why go see the doctor?\n#Person1#: Well, the best way to avoid serious illnesses is to find out about them early. So try to come at least once a year for your own good.\n#Person2#: Ok.\n#Person1#: Let me see here. Your eyes and ears look fine. Take a deep breath, please. Do you smoke, Mr. Smith?\n#Person2#: Yes.\n#Person1#: Smoking is the leading cause of lung cancer and heart disease, you know. You really should quit.\n#Person2#: I've tried hundreds of times, but I just can't seem to kick the habit.\n#Person1#: Well, we have classes and some medications that might help. I'll give you more information before you leave.\n#Person2#: Ok, thanks doctor.",
+        "summary": "Mr. Smith's getting a check-up, and Doctor Hawkins advises him to have one every year. Hawkins'll give some information about their classes and medications to help Mr. Smith quit smoking.",
+        "topic": "get a check-up"
+    },
+    {
+        "fname": "train_1",
+        "dialogue": "#Person1#: Hello Mrs. Parker, how have you been?\n#Person2#: Hello Dr. Peters. Just fine thank you. Ricky and I are here for his vaccines.\n#Person1#: Very well. Let's see, according to his vaccination record, Ricky has received his Polio, Tetanus and Hepatitis B shots. He is 14 months old, so he is due for Hepatitis A, Chickenpox and Measles shots.\n#Person2#: What about Rubella and Mumps?\n#Person1#: Well, I can only give him these for now, and after a couple of weeks I can administer the rest.\n#Person2#: OK, great. Doctor, I think I also may need a Tetanus booster. Last time I got it was maybe fifteen years ago!\n#Person1#: We will check our records and I'll have the nurse administer and the booster as well. Now, please hold Ricky's arm tight, this may sting a little.",
+        "summary": "Mrs Parker takes Ricky for his vaccines. Dr. Peters checks the record and then gives Ricky a vaccine.",
+        "topic": "vaccines"
+    },
+    {
+        "fname": "train_2",
+        "dialogue": "#Person1#: Excuse me, did you see a set of keys?\n#Person2#: What kind of keys?\n#Person1#: Five keys and a small foot ornament.\n#Person2#: What a shame! I didn't see them.\n#Person1#: Well, can you help me look for it? That's my first time here.\n#Person2#: Sure. It's my pleasure. I'd like to help you look for the missing keys.\n#Person1#: It's very kind of you.\n#Person2#: It's not a big deal.Hey, I found them.\n#Person1#: Oh, thank God! I don't know how to thank you, guys.\n#Person2#: You're welcome.",
+        "summary": "#Person1#'s looking for a set of keys and asks for #Person2#'s help to find them.",
+        "topic": "find keys"
+    },
+    {
+        "fname": "train_3",
+        "dialogue": "#Person1#: Why didn't you tell me you had a girlfriend?\n#Person2#: Sorry, I thought you knew.\n#Person1#: But you should tell me you were in love with her.\n#Person2#: Didn't I?\n#Person1#: You know you didn't.\n#Person2#: Well, I am telling you now.\n#Person1#: Yes, but you might have told me before.\n#Person2#: I didn't think you would be interested.\n#Person1#: You can't be serious. How dare you not tell me you are going to marry her?\n#Person2#: Sorry, I didn't think it mattered.\n#Person1#: Oh, you men! You are all the same.",
+        "summary": "#Person1#'s angry because #Person2# didn't tell #Person1# that #Person2# had a girlfriend and would marry her.",
+        "topic": "have a girlfriend"
+    },
+    {
+        "fname": "train_4",
+        "dialogue": "#Person1#: Watsup, ladies! Y'll looking'fine tonight. May I have this dance?\n#Person2#: He's cute! He looks like Tiger Woods! But, I can't dance. . .\n#Person1#: It's all good. I'll show you all the right moves. My name's Malik.\n#Person2#: Nice to meet you. I'm Wen, and this is Nikki.\n#Person1#: How you feeling', vista? Mind if I take your friend'round the dance floor?\n#Person2#: She doesn't mind if you don't mind getting your feet stepped on.\n#Person1#: Right. Cool! Let's go!",
+        "summary": "Malik invites Nikki to dance. Nikki agrees if Malik doesn't mind getting his feet stepped on.",
+        "topic": "dance"
+    }
+]

dialogue-summarization/ECTSum/README.md

@@ -0,0 +1,62 @@
+# ECTSum: A New Benchmark Dataset For Bullet Point Summarization of Long Earnings Call Transcripts
+
+Long Paper Accepted at the <b> EMNLP 2022 Main Conference! </b> <br /> 
+<li> Paper: https://aclanthology.org/2022.emnlp-main.748/ </li>
+<li> Poster: https://rajdeep345.github.io/files/pdf/research/ECTSum_EMNLP2022_Poster.pdf </li>
+<li> Pre-recorded Video: https://drive.google.com/file/d/1DW2i2ApgiE6V7ViiayX5zdJSRXdAEbsy/view </li>
+
+## Dataset
+The <b> <i> ECTSum </b> </i> dataset can be found under the `data` folder.
+
+## Codes
+Codes and instructions for our proposed model <b> <i> ECT-BPS </b> </i> can be found under `codes/ECT-BPS` <br />
+Codes and instructions for our baseline models can be found under `codes/baselines`
+
+
+
+## Data Preparation for ECT-BPS
+### Preparing the data for training the <i> Extractive Module </i>
+
+#### Imports
+`pip install sentence-transformers` </br>
+`pip install num2words` </br>
+`pip install word2number` </br>
+
+#### Prepare the data
+`python prepare_data_ectbps_ext.py`
+
+#### Data Location
+The data is saved at `codes/ECT-BPS/ectbps_ext/data/`. </br>
+Processed data is already uploaded at this location.
+
+
+### Preparing the data for training the <i> Paraphrasing Module </i>
+
+#### Imports
+`pip install sentence-transformers` </br>
+`pip install num2words` </br>
+`pip install word2number` </br>
+
+#### Prepare the data
+`python prepare_data_ectbps_para.py`
+
+#### Data Location
+The data is saved at `codes/ECT-BPS/ectbps_para/data/para/`. </br>
+Processed data is already uploaded at this location.
+
+#### Prepare the data with numericals masked
+`python prepare_data_ectbps_para_mask.py`
+
+#### Data Location
+The data is saved at `codes/ECT-BPS/ectbps_para/data/para_mask/`. </br>
+Processed data is already uploaded at this location.
+
+
+
+## Updates
+<li> 1st November 2022 - ECTSum Dataset released </li>
+<li> 30th November 2022 - Codes and Instructions released for training the Extractive Module of ECT-BPS </li>
+<li> 3rd March 2023 - Added the Prediction Pipeline for the Extractive module. </li>
+<li> 5th March 2023 - Codes released to prepare the data for training the Paraphrasing Module </li>
+<li> 7th March 2023 - Codes released to train the Paraphrasing Module of ECT-BPS</li>
+<li> 8th March 2023 - Google Colab Notebook released for training and testing the Paraphrasing Module </li>

dialogue-summarization/ECTSum/original_examples.json

@@ -0,0 +1,161 @@
+[
+    {
+        "file_name": "PNW_q3_2021.txt",
+        "ect": [
+            "First, I need to cover a few details with you.",
+            "We will be advancing the slides as the speakers present today.",
+            "It will also be available by telephone through November 12, 2021.",
+            "These are indeed challenging times for us.",
+            "But right upfront, I want to make it clear that while we may be navigating some short-term challenges, as you'll see, the mid-term prospects post 2022 are positive, and we remain confident in our ability to create renewed growth and deliver strong shareholder returns.",
+            "I know the conclusion of the 2019 rate case is the most significant development and everyone is interested in hearing more about that.",
+            "But before we cover the rate case, you can see from the four main topics we will discuss today.",
+            "I'll cover our third quarter results and our expectations for the remainder of 2021.",
+            "Finally, I will wrap up with 2022 guidance and our long-term financial outlook.",
+            "Focusing on the third quarter, our performance remains strong, earning $3 per share compared to $3.07 per share in third quarter of 2020.",
+            "Mild weather was a significant factor, largely offset by strong sales.",
+            "We experienced a mild July and August driven by one of the wettest monsoon seasons in recent history.",
+            "Residential cooling degree days in the third quarter decreased 27.5% compared to the same time a year ago, and were 10.6% lower than historical 10-year averages.",
+            "As a reminder, third quarter last year was the hottest on record.",
+            "Robust sales and usage growth in addition increased transmission sales this quarter mitigated most of the weather impacts.",
+            "Looking at full year, I'll provide an update to the 2021 Key Drivers and earnings guidance.",
+            "Customer growth and weather normalized sales growth remain important drivers for the remainder of the year.",
+            "We are updating weather normalized sales guidance to 3% to 4%, up from 1% to 2%, based on continued robust customer growth and strong residential usage.",
+            "Lastly, with the conclusion of the 2019 rate case, we're now able to provide full year guidance.",
+            "We expect earnings per share to be within the range of $5.25 to $5.35 per share.",
+            "As all of you know, after a series of open meetings and public discussions, the Commission issued a final decision in our 2019 rate case.",
+            "This rate case was complex and the issues were numerous.",
+            "I'll highlight a few of the main issues that were decided, the revenue requirement SCRs and the ROE.",
+            "I'll also discuss our next step and strategy coming out of this case, and then lastly as Ted mentioned, he'll provide the 2022 guidance and our long-term financial outlook.",
+            "This outcome was not what we wanted and the process that transpired was not constructive.",
+            "Everything we have said on the record with our regulators about what's so damaging and concerning about this decision holds true.",
+            "It is a decision that makes everything we're committed to doing more challenging and more costly for a time.",
+            "What this decision has not done is change our mission as a company, nor our commitment to delivering value to our customers and you our investors.",
+            "It has not changed the commitment of our employees to operational excellence in all that we do.",
+            "In fact, we're using the expertise and the track record that we've built in the areas of long-term planning, cost management, innovation and serving as an active voice and advocate for the Arizona business community to emerge from this case with a robust strategy.",
+            "We're not apologetic about standing up for what's right for our customers and our communities and for our investors, the owners of this company.",
+            "It's your confidence in us and your investment in us that makes it possible to deliver the product and services that power Arizona's economy and way of life.",
+            "We don't take that for granted and we'll lay out for you today how we plan to continue to create values at competitive levels, amid the headwinds and the challenges that this case has created.",
+            "As a reminder, this case was unique for many reasons.",
+            "We are compelled by the Commission to file this case under a question of whether we are over earning.",
+            "We are also required to fully litigate this case instead of pursuing settlement opportunities.",
+            "This is our first fully litigated rate case in over 15 years.",
+            "We still believe that rate case settlements are the standard and this case was definitely an exception.",
+            "And finally this case was centered around cost recovery of coal asset.",
+            "In contrast, our future investment recovery will be premised on infrastructure supporting Clean Energy and our customer growth.",
+            "Let me walk through some of the major decisions of the case.",
+            "First, the Commission adopted a total base rate decrease of $119 million inclusive of fuel.",
+            "The Commission did reverse its initial vote to move the SCR issue to a separate proceeding and instead provided partial recovery of the SCRs with the disallowance of $216 million.",
+            "We disagree with the Commission's decision that the SCR investment was imprudent and don't believe that the record in this case supports that conclusion.",
+            "As I've stated before the Four Corners Power Plant is a critically important reliability asset for the entire Southwest region.",
+            "It's used in useful currently serving customers and the investment in the SCRs was required to keep the plant running under federal law.",
+            "In addition, the Commission voted to lower the ROE from the recommended opinion orders already low ROE of 9.16% to 8.7%.",
+            "With this part of the decision, the Commission has adopted an ROE that's meaningfully below the national average of 9.4% for electric utilities and the company disagrees with the Commission's rationale.",
+            "We have embraced a culture focused on customer service and don't believe that a penalty was warranted, and the ROE granted ignores the fact that we were one of the fastest growing states in the country and we need to attract capital in order to fund the growth and economic development that we're experiencing in Arizona.",
+            "In addition, the Commission moved away from the long-standing practice of providing a risk premium for serving as the operator of the largest clean nuclear generating station in the country.",
+            "We'll continue to navigate through these challenges by leveraging our strong growth and seeking judicial review of the decision through the courts.",
+            "Although we are disappointed by the Commission's decision, importantly, we now have clarity of the path forward.",
+            "And so, let me share our next steps and strategy as we look to the future.",
+            "We continue to remain optimistic about our future for many reasons and I'll discuss each of these reasons in more detail.",
+            "First, we have a solid track record for performance and have grown earnings and our dividends steadily throughout this time, although we're looking at a reset with this rate case outcome and despite the challenges of our regulatory environment, both for Arizona and our company, we believe that we have the ability to create long-term value and steady growth from here.",
+            "And Ted will later share our financial outlook and the actions that we're taking as a management team to get us there.",
+            "In addition to our earnings track record, we've delivered on our promise to provide affordable energy to our customers and I'll share I think a great example.",
+            "We've seen a 6% weather normalized increase in demand for residential electricity from 2018 to 2020.",
+            "During that same period we've lowered the average residential customer bill by more than 7%.",
+            "We remain focused on customer affordability and keeping it central to our plans to provide long-term sustainable growth.",
+            "That focus, coupled with continued cost management creates headroom for the future.",
+            "The second reason that I'm optimistic about our future is our best-in-class service territory.",
+            "Arizona remains among the fastest growing states in the country, where other states were experiencing little or negative customer growth, we're projecting 1.5% to 2.5% retail customer growth in 2021 and 3% to 4% weather normalized sales growth.",
+            "We expect 43,000 housing permits this year in Maricopa County alone, levels that have not been reached since before the great recession.",
+            "We believe the constructive business environment and the ample job growth that it creates a competitive cost of living and a desirable climate will continue to grow the Metro Phoenix housing market and benefit the local economy.",
+            "Focusing on our service territory specifically, we continue to see development from a variety of sectors, which is helping to diversify our local economy more than ever.",
+            "In particular, Phoenix is becoming a leader in attracting high tech and data center customers.",
+            "As you may remember, Taiwan Semiconductor broke ground on their $12 billion investment earlier this year, cementing Phoenix is one of the top semiconductor hubs in the country.",
+            "More recently, KORE Power announced their intention to build a 1 million square foot lithium-ion battery manufacturing facility.",
+            "We'll continue to focus our economic development approach on helping to attract and expand businesses and job creators.",
+            "The third reason that we're confident is the clear path for our transition to Clean Energy.",
+            "We came out with our Clean Energy commitment in early 2020, and I'm proud that we've made significant progress toward that commitment.",
+            "As you know, earlier this year, we announced that our Four Corners power plant would begin seasonal operations in 2023.",
+            "This will reduce annual carbon emissions from the plant by an estimated 20% to 25% compared to current conditions.",
+            "In addition, we remain committed to end the use of coal at our remaining Cholla units by 2025 and to completely exit coal by 2031.",
+            "Since our Clean Energy commitments announcement we've procured nearly 1,400 megawatts of additional Clean Energy and storage.",
+            "Obviously, Arizona enjoys some of the best solar conditions in the world and we are well positioned to capitalize on this resource as we continue that Clean Energy transition.",
+            "Turning to our regulatory environment.",
+            "Although, this last case was not constructive, I believe we'll be able to reasonably navigate through the regulatory environment in the future.",
+            "I'll underscore that this last case was unique in nearly every aspect.",
+            "We plan on filing a new rate case as soon as practicable and be looking to improve the ROE commensurate with rising interest rates and returns.",
+            "Historically, outcomes achieved through settlement have delivered new and innovative customer programs and other results that benefit a broad and a diverse range of vested interest in our state's energy future.",
+            "We would aim to achieve a settled outcome in our next case, because we believe that the nature of that process itself yields more informed constructive and mutually beneficial results.",
+            "We'll work to find alignment with stakeholders and the regulators, so that we can improve things for all interested parties.",
+            "Finally, I'm optimistic about the future because we have a well thought out long-term strategy that my entire management team and I are committed to executing.",
+            "We've refocused on the customer and have built a customer-centric strategy that will allow us to deliver exceptional customer service results.",
+            "We are the most improved large utility in J.D. Power's 2020 residential electric service study and we're focused on making continued improvements.",
+            "Near term, our focus and priorities remain on improving our customer experience, customer communications, providing safe and reliable service and continuing to engage with stakeholders to advance our shared priorities of clean, reliable and affordable energy for Arizona residents and businesses.",
+            "Now, I'll walk through our 2022 guidance and long-term financial outlook.",
+            "As Jeff discussed, this last case was not the outcome we were looking for and we recognize this rate case is a regulatory reset.",
+            "We're providing a 2022 earnings guidance range of $3.80 to $4 per share given the full effects of the rate case.",
+            "We recognize this is a significant reduction compared to 2021, so we've illustrated key factors contributing to the change in earnings.",
+            "As you can see on Slide 19, we're starting with the midpoint of our 2021 guidance and walking through the drivers to get us to the midpoint of our 2022 guidance.",
+            "No surprise, the most significant driver is the recent rate case decision, with a negative $0.90 impact.",
+            "This reflects an additional $13 million downward adjustment beyond the $90 million net income impact estimated for the recommended opinion on order last quarter.",
+            "In addition, growth in depreciable plant, higher interest expense related to new financing needs and lower pension OPEB non service credits make up the remaining negative drivers.",
+            "We are focused on cost management and expect O&M savings to provide some positive impact to get us to our 2022 guidance range of $3.80 to $4 per share.",
+            "Turning to the future, we are prepared to use all levers we have available to help us mitigate the impact of this case, and we remain optimistic of our ability to provide long-term value.",
+            "As you can see, investors can expect seven objectives from us and I'll touch upon each one.",
+            "Our plan is expected to provide strong long-term earnings growth after 2022 for the next five years.",
+            "I want to be transparent and reemphasize that this as projected 5% to 7% earnings growth, builds on our 2022 guidance.",
+            "We realize the 2021 base year is a lower growth rate at about 1% to 2%.",
+            "However, we believe 2022 is the appropriate place to anchor our long-term outlook given the valuation reset that has already occurred and we're focused on creating shareholder value from this point going forward.",
+            "There are a number of factors that could provide upside potential to our growth guidance.",
+            "For example, we have the ability to meet -- we have the ability to invest in more Clean Energy if we achieve more constructive cost recovery.",
+            "In addition, robust economic development opportunities may drive increased sales and customer growth.",
+            "Those along with other factors could provide upside to our guidance.",
+            "The second objective shareholders can expect from us, is an optimized capital management plan.",
+            "As Jeff discussed, we continued to experience solid growth in our service territory, which is the primary driver behind our capital plan.",
+            "Steady population growth is expected to drive average annual customer growth in the range of 1.5% to 2.5% through 2024.",
+            "In addition, we expect average annual sales growth to be in the range of 3.5% to 4.5% through 2024 on a weather-normalized basis.",
+            "We have updated our capital plan to $4.7 billion from 2022 to 2024.",
+            "While this represents a modest increase from prior levels, we believe this is prudent until we're in a better place to secure timely and constructive cost recovery.",
+            "We are committed to taking a balanced approach in managing our capital plan to support customer growth, reliability and our clean transition, while limiting our equity needs to minimize dilution as we recover from the outcome of this case.",
+            "Third, as you can see from 2019 to 2024, we project that our rate base growth will remain steady at an average annual growth rate of 5% to 6%.",
+            "I want to highlight that our FERC jurisdictional transmission investments continue to represent a meaningful portion of that growth, that almost a quarter of the total rate base.",
+            "These investments benefit from superior authorized returns in a more favorable cost recovery construct than our ACC jurisdictional investments.",
+            "We believe the steady growth will allow us the opportunity to provide solid earnings growth from transmission in the future.",
+            "Next, I'd like to provide clarity on our financing plans going forward.",
+            "We've previously stated that we would issue equity prior to the next rate case.",
+            "We understand this case was not constructive and we're committed to doing everything we can to protect shareholders from further dilution.",
+            "Therefore, we're deferring our equity issuance and have no plans to issue equity until the conclusion of the next rate case.",
+            "In the meantime, we'll leverage our sales growth and the strength of our balance sheet to support our investment needs.",
+            "While we show equity or equity alternatives in the plan, we have no plans for this to be sourced earlier than 2024, protecting investors from dilution during this period.",
+            "We have a solid track record of disciplined cost management and previously announced that we have initiated additional cost savings programs.",
+            "We understand the importance of efficiency and instituting lean initiatives.",
+            "With that in mind, we're updating our O&M guidance to show one, a reduction of O&M expense from 2021 to 2022.",
+            "Two, a goal of keeping total O&M flat during this period.",
+            "And three, a goal of declining O&M per kilowatt hour.",
+            "Cost management and lean processes will continue to be a strong focus of our management team to mitigate both inflationary pressures and regulatory lag.",
+            "We anticipate another important expectation that investors can look forward to as our attractive dividend yield.",
+            "Yesterday, our Board of Directors announced an increase in our quarterly shareholder dividend from $0.83 to $0.85 per share.",
+            "We have consistently grown our dividend for 10 years straight and we are committed to dividend growth going forward.",
+            "Our longer term objective is to grow the dividend, commensurate with earnings growth and target a long-term dividend payout ratio of 65% to 75%.",
+            "We understand that we're not there now, but we are confident in our plan and that we will eventually grow back into this payout range.",
+            "Turning to the final item, our balance sheet.",
+            "We continue to maintain a strong balance sheet, providing us flexibility in our sources of capital over the next few years.",
+            "We have an attractive long-term debt maturity profile and no debt maturing at APS until 2024.",
+            "Additionally, we maintain robust and durable sources of liquidity with our $1.2 billion of credit facilities recently extended to 2026 and a well-funded and largely derisked pension.",
+            "Taking a closer look at our ratings.",
+            "We continue to have solid investment grade credit ratings.",
+            "Even with the recent downgrade by Fitch and the credit reviews announced by Moody's and S&P, our balance sheet targets include three key components, maintaining credit rating strength, maintaining an APS equity layer greater than 50% and an FFO to debt range of 16% to 18%.",
+            "In summary, we're taking action during this reset and have a plan for attractive growth going forward.",
+            "Importantly, we plan to defer all equity until 2024, further reduce O&M and optimize the balance sheet and capital program during this reset period.",
+            "In return, we have the highest dividend yield among peers, which stands today above 5%.",
+            "While certainly a factor of the current valuation, even at a stock price 20% higher than current levels, we offer a dividend yield more competitive than peers.",
+            "In addition, we announced long-term earnings per share growth guidance of 5% to 7% from 2022 for the next five years.",
+            "With the attractive dividend yield and solid earnings per share CAGR, we anticipate a competitive 10% to 12% total shareholder return going forward.",
+            "In the short-term, we are laser focused on doing everything we can to protect investors during this reset period and then transitioning to a renewed era of growth, so that we can provide a competitive return going forward.",
+            "We remain optimistic about the future.",
+            "Although the final outcome of this rate case was worse than we had expected, we have a path forward that is centered around our long-term track record of constructive rate case outcomes, our robust service territory growth, continued balance sheet strength and a focused management team that is taking action."
+        ],
+        "summary": [
+            "sees fy earnings per share $5.25 to $5.35 from continuing operations."
+        ]
+    }
+]

dialogue-summarization/ICSI/README.md

@@ -0,0 +1,22 @@
+# ICSI Corpus
+
+[The Meeting Recorder Project](https://www1.icsi.berkeley.edu/Speech/mr/mtgrcdr.html)
+
+Despite recent advances in speech recognition technology, successful recognition is limited to co-operative speakers using close-talking microphones. There are, however, many other situations in which speech recognition would be useful - for instance to provide transcripts of meetings or other archive audio. Speech researchers at ICSI, UW, SRI, and IBM are very interested in new application domains of this kind, and we have begun to work with recorded meeting data.
+
+The first stage in investigating speech recognition for meetings is to collect some data. At ICSI, we have equipped a meeting room with a multichannel, studio-quality recording system and have begun to collect pilot recordings of meetings, primarily between speech group members. At the time of writing (2001 February), we have collected 40 hours of 16 channel pilot data, and ten hours has been hand-transcribed. See this information on Meeting Recorder data collection including both the mechanics of the meeting recorder setup at ICSI and some initial forays into processing the recordings. The data were then transcribed, using a set of transcription conventions designed for speed and accuracy of data input and encoding.
+
+Transcribers used a version of the "Transcriber" interface, modified in two ways to handle multi-channel inputs and overlapping speech. For information on our modifications of the Transcriber tool, including screen shots, see here.
+
+An example of the differences between a high-quality, near-field, head-worn microphone and a far-field, desktop microphone is also available.
+A key issue in the project is to specify the goals and applications. While the basic idea is to develop recognition that could transcribe conventional meetings, this would be useful only in so far as it would support applications such as searching for particular information or producing automatic summaries. Here is an introduction to Meeting Recorder: Portable Speech Recognition, which particularly discusses applications for a meeting recorder that could be made portable i.e. like a PDA.
+
+This project is a collaboration between the ICSI speech group (aka Realization), the SSLI lab at the University of Washington (as part of their Communicator project work), and SRI's STAR Lab. Primary funding currently comes from DARPA, and IBM will be providing further support via both collaboration and funding.
+
+### Citation:
+
+The data is originally from [The ICSI Meeting Corpus](https://groups.inf.ed.ac.uk/ami/icsi/index.shtml), and the corresponding website is [link](https://groups.inf.ed.ac.uk/ami/icsi/index.shtml).
+
+We further process the data based on https://github.com/guokan-shang/ami-and-icsi-corpora.
+
+Please cite their work accordingly if you use the dataset. Thank you!