Switch to loading script

README.md

@@ -1,43 +1,189 @@
 ---
 license: cc-by-4.0
 task_categories:
-- text-classification
-- zero-shot-classification
+  - text-classification
+  - zero-shot-classification
+task_ids:
+  - multi-label-classification
 language:
-- en
+  - en
 tags:
-- Human Values
-- Value Detection
-- Multi-Label
+  - Human Values
+  - Value Detection
+  - Multi-Label
 pretty_name: Human Value Detection Dataset
 size_categories:
-- 1K<n<10K
+  - 1K<n<10K
 ---
+# The Touch&eacute;23-ValueEval Dataset
 
-Touché23-ValueEval
-==================
-[link](https://webis.de/data.html#touche23-valueeval)
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Dataset Usage](#dataset-usage)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+    - [Argument Instances](#argument-instances)
+    - [Metadata Instances](#metadata-instances)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
 
-Usage:
-```
-from datasets import load_dataset
-import ast
+## Dataset Description
 
-def convert_labels(example):
-    example["Labels"] = [i for i in ast.literal_eval(example["Labels"])]
-    return example
+- **Homepage:** [https://webis.de/data/touche23-valueeval.html](https://webis.de/data/touche23-valueeval.html)
+- **Repository:** [https://doi.org/10.5281/zenodo.6814563](https://doi.org/10.5281/zenodo.6814563)
+- **Paper:** [The Touch&eacute;23-ValueEval Dataset for Identifying Human Values behind Arguments.](https://webis.de/downloads/publications/papers/mirzakhmedova_2023a.pdf)
+- **Leaderboard:** [https://touche.webis.de/](https://touche.webis.de/)
+- **Point of Contact:** [Webis Group](https://webis.de/people.html)
 
-valueeval23 = load_dataset("webis/Touche23-ValueEval")
+### Dataset Summary
 
-training_dataset = valueeval23["training"].map(convert_labels)
-```
+The Touch&eacute;23-ValueEval Dataset comprises 9324 arguments from six different sources. An arguments source is indicated with the first letter of its `Argument ID`:
+- `A`: [IBM-ArgQ-Rank-30kArgs](https://research.ibm.com/haifa/dept/vst/debating_data.shtml#Argument%20Quality)
+- `C`:Chinese question-answering website [Zhihu](https://www.zhihu.com)
+- `D`:[Group Discussion Ideas (GD IDEAS)](https://www.groupdiscussionideas.com)
+- `E`:[The Conference for the Future of Europe](https://futureu.europa.eu)
+- `F`:Contribution by the language.ml lab (Doratossadat, Omid, Mohammad, Ehsaneddin) [1]:
+    arguments from the "Nahj al-Balagha" [2] and "Ghurar al-Hikam wa Durar ak-Kalim" [3]
+- `G`:[The New York Times](https://www.nytimes.com)
 
-See available dataset parts:
-```
-valueeval23
+The annotated labels are based on the value taxonomy published in
+[Identifying the Human Values behind Arguments](https://webis.de/publications.html#kiesel_2022b) (Kiesel et al. 2022) at ACL'22.
+
+[1] https://language.ml
+[2] https://en.wikipedia.org/wiki/Nahj_al-Balagha
+[3] https://en.wikipedia.org/wiki/Ghurar_al-Hikam_wa_Durar_al-Kalim
+
+### Dataset Usage
+
+The default configuration name is `main`.
+```python
+from datasets import load_dataset
+dataset = load_dataset("webis/Touche23-ValueEval")
+print(dataset['train'].info.description)
+for argument in iter(dataset['train']):
+    print(f"{argument['Argument ID']}: {argument['Stance']} '{argument['Conclusion']}': {argument['Premise']}")
 ```
 
-The `Labels` for each example is an array of 1s (argument resorts to value) and 0s (argument does not resort to value). The order is the same as in the original files:
+### Supported Tasks and Leaderboards
+
+Human Value Detection
+
+### Languages
+
+The [Argument Instances](#argument-instances) are all monolingual; it only includes English (mostly en-US) documents.
+The [Metadata Instances](#metadata-instances) for some dataset parts additionally state the arguments in their original language and phrasing.
+
+## Dataset Structure
+
+### Argument Instances
+
+Each argument instance has the following attributes:
+- `Argument ID`: The unique identifier for the argument within the dataset
+- `Conclusion`: Conclusion text of the argument
+- `Stance`: Stance of the `Premise` towards the `Conclusion; one of "in favor of", "against"
+- `Premise`: Premise text of the argument
+- `Labels`: The `Labels` for each example is an array of 1s (argument resorts to value) and 0s (argument does not resort to value). The order is the same as in the original files.
+
+Additionally, the labels are separated into *value-categories*, aka. level 2 labels of the value taxonomy (Kiesel et al. 2022b), and *human values*, aka. level 1 labels of the value taxonomy.
+This distinction is also reflected in the configuration names:
+- `<config>`: As the [Task](https://touche.webis.de/semeval23/touche23-web/) is focused mainly on the detection of value-categories,
+    each base configuration ([listed below](#p-list-base-configs)) has the 20 value-categories as labels:
+  ```python
+  labels = ["Self-direction: thought", "Self-direction: action", "Stimulation", "Hedonism", "Achievement", "Power: dominance", "Power: resources", "Face", "Security: personal", "Security: societal", "Tradition", "Conformity: rules", "Conformity: interpersonal", "Humility", "Benevolence: caring", "Benevolence: dependability", "Universalism: concern", "Universalism: nature", "Universalism: tolerance", "Universalism: objectivity"]
+  ```
+- `<config>-level1`: The 54 human values from the level 1 of the value taxonomy are not used for the 2023 task
+    (except for the annotation), but are still listed here for some might find them useful for understanding the value
+    categories. Their order is also the same as in the original files. For more details see the [value-categories](#metadata-instances) configuration.
+
+<p id="p-list-base-configs">The configuration names (as replacements for <code>&lt;config&gt;</code>) in this dataset are:</p>
+
+- `main`: 8865 arguments (sources: `A`, `D`, `E`) with splits `train`, `validation`, and `test`
+- `nahjalbalagha`: 279 arguments (source: `F`) with split `test`
+- `nyt`: 80 arguments (source: `G`) with split `test`
+- `zhihu`: 100 arguments (source: `C`) with split `validation`
+
+Please note that due to copyright reasons, there currently does not exist a direct download link to the arguments contained in the
+New york Times
+dataset. Accessing any of the `nyt` or `nyt-level1` configurations will therefore use the specifically created
+[nyt-downloader program](https://github.com/touche-webis-de/touche-code/tree/main/semeval23/human-value-detection/nyt-downloader)
+to create and access the arguments locally. See the program's
+[README](https://github.com/touche-webis-de/touche-code/blob/main/semeval23/human-value-detection/nyt-downloader/README.md)
+for further details.
+
+### Metadata Instances
+
+The following lists all configuration names for metadata. Each configuration only has a single split named `meta`.
+- `ibm-meta`: Each row corresponds to one argument (IDs starting with `A`) from the [IBM-ArgQ-Rank-30kArgs](https://research.ibm.com/haifa/dept/vst/debating_data.shtml#Argument%20Quality)
+    - `Argument ID`: The unique identifier for the argument
+    - `WA`: the quality label according to the weighted-average scoring function
+    - `MACE-P`: the quality label according to the MACE-P scoring function
+    - `stance_WA`: the stance label according to the weighted-average scoring function
+    - `stance_WA_conf`: the confidence in the stance label according to the weighted-average scoring function
+- `zhihu-meta`: Each row corresponds to one argument (IDs starting with `C`) from the Chinese question-answering website [Zhihu](https://www.zhihu.com)
+    - `Argument ID`: The unique identifier for the argument
+    - `Conclusion Chinese`: The original chinese conclusion statement
+    - `Premise Chinese`: The original chinese premise statement
+    - `URL`: Link to the original statement the argument was taken from
+- `gdi-meta`: Each row corresponds to one argument (IDs starting with `D`) from [GD IDEAS](https://www.groupdiscussionideas.com/)
+    - `Argument ID`: The unique identifier for the argument
+    - `URL`: Link to the topic the argument was taken from
+- `cofe-meta`: Each row corresponds to one argument (IDs starting with `E`) from [the Conference for the Future of Europe](https://futureu.europa.eu)
+    - `Argument ID`: The unique identifier for the argument
+    - `URL`: Link to the comment the argument was taken from
+- `nahjalbalagha-meta`: Each row corresponds to one argument (IDs starting with `F`). This file contains information on the 279 arguments in `nahjalbalagha` (or `nahjalbalagha-level1`)
+    and 1047 additional arguments that were not labeled so far. This data was contributed by the language.ml lab.
+    - `Argument ID`: The unique identifier for the argument
+    - `Conclusion Farsi`: Conclusion text of the argument in Farsi
+    - `Stance Farsi`: Stance of the `Premise` towards the `Conclusion`, in Farsi
+    - `Premise Farsi`: Premise text of the argument in Farsi
+    - `Conclusion English`: Conclusion text of the argument in English (translated from Farsi)
+    - `Stance English`: Stance of the `Premise` towards the `Conclusion`; one of "in favor of", "against"
+    - `Premise English`: Premise text of the argument in English (translated from Farsi)
+    - `Source`: Source text of the argument; one of "Nahj al-Balagha", "Ghurar al-Hikam wa Durar ak-Kalim"; their Farsi translations were used
+    - `Method`: How the premise was extracted from the source; one of "extracted" (directly taken), "deduced"; the conclusion are deduced
+- `nyt-meta`: Each row corresponds to one argument (IDs starting with `G`) from [The New York Times](https://www.nytimes.com)
+    - `Argument ID`: The unique identifier for the argument
+    - `URL`: Link to the article the argument was taken from
+    - `Internet Archive timestamp`: Timestamp of the article's version in the Internet Archive that was used
+- `value-categories`: Contains a single JSON-entry with the structure of level 2 and level 1 values regarding the value taxonomy:
+  ```
+  {
+    "<value category>": {
+      "<level 1 value>": [
+        "<exemplary effect a corresponding argument might target>",
+        ...
+      ], ...
+    }, ...
+  }
+  ```
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+[Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)
+
+### Citation Information
+
 ```
-labels = ["Self-direction: thought", "Self-direction: action", "Stimulation", "Hedonism", "Achievement", "Power: dominance", "Power: resources", "Face", "Security: personal", "Security: societal", "Tradition", "Conformity: rules", "Conformity: interpersonal", "Humility", "Benevolence: caring", "Benevolence: dependability", "Universalism: concern", "Universalism: nature", "Universalism: tolerance", "Universalism: objectivity"]
+@Article{mirzakhmedova:2023a,
+  author    = {Nailia Mirzakhmedova and Johannes Kiesel and Milad Alshomary and Maximilian Heinrich and Nicolas Handke\
+and Xiaoni Cai and Valentin Barriere and Doratossadat Dastgheib and Omid Ghahroodi and {Mohammad Ali} Sadraei\
+and Ehsaneddin Asgari and Lea Kawaletz and Henning Wachsmuth and Benno Stein},
+  doi       = {10.48550/arXiv.2301.13771},
+  journal   = {CoRR},
+  month     = jan,
+  publisher = {arXiv},
+  title     = {{The Touch{\'e}23-ValueEval Dataset for Identifying Human Values behind Arguments}},
+  volume    = {abs/2301.13771},
+  year      = 2023
+}
 ```

Touche23-ValueEval.py

@@ -0,0 +1,737 @@
+# Copyright 2023 The Touché23-ValueEval Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://creativecommons.org/licenses/by/4.0/legalcode
+
+"""The Touch\u00E923-ValueEval Dataset"""
+
+import json
+import pandas as pd
+import os
+import sys
+import subprocess
+
+import datasets
+
+
+_DESCRIPTION = """\
+Dataset for Touch\u00E9 / SemEval 2023 Task 4; ValueEval: Identification of Human Values behind Arguments:
+https://www.overleaf.com/6679855346wrdckzkdccxg
+Based on the original Webis-ArgValues-22 (https://doi.org/10.5281/zenodo.5657249) dataset accompanying the paper
+Identifying the Human Values behind Arguments (Kiesel et al. 2022b; https://webis.de/publications.html#kiesel_2022b),
+published at ACL'22.
+
+"""
+
+_CITATION = """\
+@Article{mirzakhmedova:2023a,
+  author    = {Nailia Mirzakhmedova and Johannes Kiesel and Milad Alshomary and Maximilian Heinrich and Nicolas Handke\
+and Xiaoni Cai and Valentin Barriere and Doratossadat Dastgheib and Omid Ghahroodi and {Mohammad Ali} Sadraei\
+and Ehsaneddin Asgari and Lea Kawaletz and Henning Wachsmuth and Benno Stein},
+  doi       = {10.48550/arXiv.2301.13771},
+  journal   = {CoRR},
+  month     = jan,
+  publisher = {arXiv},
+  title     = {{The Touch{\'e}23-ValueEval Dataset for Identifying Human Values behind Arguments}},
+  volume    = {abs/2301.13771},
+  year      = 2023
+}"""
+
+_ARGUMENT_DATASET_DESCRIPTION = """\
+Each row corresponds to an argument consisting of it's unique identifier (Argument ID) and the arguments content being
+its Premise, Stance, and Conclusion.
+"""
+
+_LEVEL1_DESCRIPTION = _ARGUMENT_DATASET_DESCRIPTION + """\
+The Labels for each example is an array of 1s (argument resorts to value) and 0s (argument does not resort to value).
+The 54 human values from the level 1 of the value taxonomy (Kiesel et al. 2022b) are not used for the 2023 task
+(except for the annotation), but are still listed here for some might find them useful for understanding the value
+categories. Their order is the same as in the original files. For more details see the 'value-categories' configuration."""
+
+_LEVEL2_DESCRIPTION = _ARGUMENT_DATASET_DESCRIPTION + """\
+The Labels for each example is an array of 1s (argument resorts to value) and 0s (argument does not resort to value).
+The order of the 20 value categories from the level 2 of the value taxonomy (Kiesel et al. 2022b)
+is the same as in the original files. For more details see the 'value-categories' configuration."""
+
+_IBM_DESCRIPTION = """\
+The 7368 arguments from the IBM-ArgQ-Rank-30kArgs corpus (Gretz et al., 2020):
+https://research.ibm.com/haifa/dept/vst/debating_data.shtml#Argument%20Quality"""
+
+_IBM_META_DESCRIPTION = """\
+Each entry corresponds to one argument (IDs starting with A) containing the data on argument quality for the respective
+argument taken from the IBM-ArgQ-Rank-30kArgs corpus."""
+
+_ZHIHU_DESCRIPTION = """\
+Supplementary set of 100 arguments from the recommendation and hotlist section of the Chinese question-answering website Zhihu:
+https://www.zhihu.com/explore
+which teams can use for training or validating more robust approaches; these have been part of the original\
+Webis-ArgValues-22 dataset."""
+
+_ZHIHU_META_DESCRIPTION = """\
+Each entry corresponds to one argument (IDs starting with C) reporting the original chinese conclusion and premise
+as well as the link to the original statement the argument was taken from."""
+
+_GROUP_DISCUSSION_IDEAS_DESCRIPTION = """\
+A set of 399 arguments from the Group Discussion Ideas (GD IDEAS) web page:
+https://www.groupdiscussionideas.com/"""
+
+_GROUP_DISCUSSION_IDEAS_META_DESCRIPTION = """\
+Each entry corresponds to one argument (IDs starting with D) reporting the link to the topic the argument was taken from."""
+
+_COFE_DESCRIPTION = """\
+A set of 1098 arguments from the Conference on the Future of Europe portal:
+https://futureu.europa.eu/
+The arguments were sampled from an existing dataset (Barriere et al., 2022)."""
+
+_COFE_META_DESCRIPTION = """\
+Each entry corresponds to one argument (IDs starting with E) reporting the link to the comment the argument was taken from."""
+
+_NAHJALBALAGHA_DESCRIPTION = """\
+Arguments from and based on the Nahj al-Balagha.
+This data was contributed by the language.ml lab (Doratossadat, Omid, Mohammad, Ehsaneddin):
+https://language.ml/"""
+
+_NAHJALBALAGHA_META_DESCRIPTION = """\
+Each entry corresponds to one argument (IDs starting with F) containing information on the 279 arguments in the dataset
+(configuration: 'nahjalbalagha') and 1047 additional arguments that were not labeled so far."""
+
+_NYT_DESCRIPTION = """\
+Supplementary set of 80 arguments from 12 news articles of The New York Times
+https://www.nytimes.com/
+that were published between July 2020 and May 2021 and contain at least one of these keywords:
+coronavirus (2019-ncov), vaccination and immunization, and epidemics."""
+
+_NYT_META_DESCRIPTION = """\
+Each entry corresponds to one argument (IDs starting with G) reporting the link to the article the argument was taken
+from and the timestamp of the article's version in the Internet Archive that was used."""
+
+_CATEGORIES_JSON_DESCRIPTION = """\
+The single JSON entry in value-categories describes the 20 value categories (level 2 of the taxonomy) of this task
+through examples. Each category maps to a dictionary of its contained level 1 values with a given list of exemplary phrases.
+The level 1 values are not used for the 2023 task (except for the annotation), but are still listed here for some might
+find them useful for understanding the value categories."""
+
+_IBM_CITATION = """\
+@inproceedings{gretz:2020,
+  author    = {Shai Gretz and Roni Friedman and Edo Cohen{-}Karlik and Assaf Toledo and Dan Lahav and Ranit Aharonov and Noam Slonim},
+  title     = {A Large-Scale Dataset for Argument Quality Ranking: Construction and Analysis},
+  booktitle = {34th {AAAI} Conference on Artificial Intelligence ({AAAI} 2020)},
+  pages     = {7805-7813},
+  publisher = {{AAAI} Press},
+  year      = {2020},
+  doi       = {10.1609/aaai.v34i05.6285},
+  url       = {https://aaai.org/ojs/index.php/AAAI/article/view/6285}
+}"""
+
+_COFE_CITATION = """\
+@inproceedings{barriere-etal-2022-cofe,
+  title = "{C}o{FE}: A New Dataset of Intra-Multilingual Multi-target Stance Classification from an Online {E}uropean Participatory Democracy Platform",
+  author = "Barriere, Valentin and Jacquet, Guillaume Guillaume and Hemamou, Leo",
+  booktitle = "Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
+  month = nov,
+  year = "2022",
+  address = "Online only",
+  publisher = "Association for Computational Linguistics",
+  url = "https://aclanthology.org/2022.aacl-short.52",
+  pages = "418--422"
+}"""
+
+_HOMEPAGE = "https://webis.de/data/touche23-valueeval.html"
+
+_LICENSE = "https://creativecommons.org/licenses/by/4.0/legalcode"
+
+
+######################################
+# START OF: Additional variables #####
+######################################
+
+_SPLIT_META = datasets.Split('meta')
+
+_CONFIG_NAME_MAIN, _CONFIG_NAME_NAHJALBALAGHA, _CONFIG_NAME_ZHIHU = "main", "nahjalbalagha", "zhihu"
+_CONFIG_NAME_MAIN_LEVEL1, _CONFIG_NAME_NAHJALBALAGHA_LEVEL1, _CONFIG_NAME_ZHIHU_LEVEL1 = "main-level1", "nahjalbalagha-level1", "zhihu-level1"
+_CONFIG_NAME_NYT, _CONFIG_NAME_NYT_LEVEL1 = "nyt", "nyt-level1"
+
+_CONFIG_NAME_META_A, _CONFIG_NAME_META_D, _CONFIG_NAME_META_E = "ibm-meta", "gdi-meta", "cofe-meta"
+_CONFIG_NAME_META_C, _CONFIG_NAME_META_F, _CONFIG_NAME_META_G = "zhihu-meta", "nahjalbalagha-meta", "nyt-meta"
+_CONFIG_NAME_VALUE_CATEGORIES = "value-categories"
+
+_SPLIT_TYPE_TRAIN, _SPLIT_TYPE_VAL, _SPLIT_TYPE_TEST = "training", "validation", "test"
+_SPLIT_TYPE_META = "meta"
+_FILE_TYPE_ARGUMENTS, _FILE_TYPE_LABELS = "arguments", "labels"
+_FILE_TYPE_META, _FILE_TYPE_JSON = "meta", "json"
+
+_FILE_TYPE_DOWNLOADER = "downloader"
+
+####################################
+# END OF: Additional variables #####
+####################################
+
+
+###########################
+# START OF: Data URLs #####
+###########################
+
+_ZENODO_LINK = "https://zenodo.org/record/7879430/files/"
+_URL = os.environ.get('TIRA_INPUT_DIRECTORY', _ZENODO_LINK)
+_NYT_DOWNLOADER_URL = "https://raw.githubusercontent.com/touche-webis-de/touche-code/main/semeval23/human-value-detection/nyt-downloader/"
+
+_NYT_ARGUMENTS_FILE_LOCAL = "webis_touche23-valueeval_arguments-test-nyt.tsv"
+_NYT_ARGUMENTS_FILE_ON_TIRA = "arguments-test-nyt.tsv"
+
+_URLS = {
+    _CONFIG_NAME_MAIN: {
+        _SPLIT_TYPE_TRAIN: {
+            _FILE_TYPE_ARGUMENTS: _URL + "arguments-training.tsv",
+            _FILE_TYPE_LABELS: _URL + "labels-training.tsv"
+        },
+        _SPLIT_TYPE_VAL: {
+            _FILE_TYPE_ARGUMENTS: _URL + "arguments-validation.tsv",
+            _FILE_TYPE_LABELS: _URL + "labels-validation.tsv"
+        },
+        _SPLIT_TYPE_TEST: {
+            _FILE_TYPE_ARGUMENTS: _URL + "arguments-test.tsv",
+            _FILE_TYPE_LABELS: _URL + "labels-test.tsv"
+        }
+    },
+    _CONFIG_NAME_MAIN_LEVEL1: {
+        _SPLIT_TYPE_TRAIN: {
+            _FILE_TYPE_ARGUMENTS: _URL + "arguments-training.tsv",
+            _FILE_TYPE_LABELS: _URL + "level1-labels-training.tsv"
+        },
+        _SPLIT_TYPE_VAL: {
+            _FILE_TYPE_ARGUMENTS: _URL + "arguments-validation.tsv",
+            _FILE_TYPE_LABELS: _URL + "level1-labels-validation.tsv"
+        },
+        _SPLIT_TYPE_TEST: {
+            _FILE_TYPE_ARGUMENTS: _URL + "arguments-test.tsv",
+            _FILE_TYPE_LABELS: _URL + "level1-labels-test.tsv"
+        }
+    },
+    _CONFIG_NAME_NAHJALBALAGHA: {
+        _SPLIT_TYPE_TEST: {
+            _FILE_TYPE_ARGUMENTS: _URL + "arguments-test-nahjalbalagha.tsv",
+            _FILE_TYPE_LABELS: _URL + "labels-test-nahjalbalagha.tsv"
+        }
+    },
+    _CONFIG_NAME_NAHJALBALAGHA_LEVEL1: {
+        _SPLIT_TYPE_TEST: {
+            _FILE_TYPE_ARGUMENTS: _URL + "arguments-test-nahjalbalagha.tsv",
+            _FILE_TYPE_LABELS: _URL + "level1-labels-test-nahjalbalagha.tsv"
+        }
+    },
+    _CONFIG_NAME_NYT: {
+        _SPLIT_TYPE_TEST: {
+            _FILE_TYPE_LABELS: _URL + "labels-test-nyt.tsv"
+        }
+    },
+    _CONFIG_NAME_NYT_LEVEL1: {
+        _SPLIT_TYPE_TEST: {
+            _FILE_TYPE_LABELS: _URL + "level1-labels-test-nyt.tsv"
+        }
+    },
+    _CONFIG_NAME_ZHIHU: {
+        _SPLIT_TYPE_VAL: {
+            _FILE_TYPE_ARGUMENTS: _URL + "arguments-validation-zhihu.tsv",
+            _FILE_TYPE_LABELS: _URL + "labels-validation-zhihu.tsv"
+        }
+    },
+    _CONFIG_NAME_ZHIHU_LEVEL1: {
+        _SPLIT_TYPE_VAL: {
+            _FILE_TYPE_ARGUMENTS: _URL + "arguments-validation-zhihu.tsv",
+            _FILE_TYPE_LABELS: _URL + "level1-labels-validation-zhihu.tsv"
+        }
+    },
+    _CONFIG_NAME_META_A: {
+        _SPLIT_TYPE_META: {
+            _FILE_TYPE_META: _URL + "meta-arguments-a.tsv"
+        }
+    },
+    _CONFIG_NAME_META_D: {
+        _SPLIT_TYPE_META: {
+            _FILE_TYPE_META: _URL + "meta-arguments-d.tsv"
+        }
+    },
+    _CONFIG_NAME_META_E: {
+        _SPLIT_TYPE_META: {
+            _FILE_TYPE_META: _URL + "meta-arguments-e.tsv"
+        }
+    },
+    _CONFIG_NAME_META_C: {
+        _SPLIT_TYPE_META: {
+            _FILE_TYPE_META: _URL + "meta-arguments-c.tsv"
+        }
+    },
+    _CONFIG_NAME_META_F: {
+        _SPLIT_TYPE_META: {
+            _FILE_TYPE_META: _URL + "meta-arguments-f.tsv"
+        }
+    },
+    _CONFIG_NAME_META_G: {
+        _SPLIT_TYPE_META: {
+            _FILE_TYPE_META: _URL + "meta-arguments-g.tsv"
+        }
+    },
+    _CONFIG_NAME_VALUE_CATEGORIES: {
+        _SPLIT_TYPE_META: {
+            _FILE_TYPE_JSON: _URL + "value-categories.json"
+        }
+    }
+}
+
+_NYT_DOWNLOADER_FILES = {
+    "requirements": _NYT_DOWNLOADER_URL + "requirements.txt",
+    "downloader": _NYT_DOWNLOADER_URL + "nyt-downloader.py",
+    "input-file": _NYT_DOWNLOADER_URL + "nyt01-spans.tsv",
+    "checksum": _NYT_DOWNLOADER_URL + "arguments-test-nyt.sha256"
+}
+if _URL != _ZENODO_LINK:
+    # running on TIRA
+    _URLS[_CONFIG_NAME_NYT][_SPLIT_TYPE_TEST][_FILE_TYPE_ARGUMENTS] = _URL + _NYT_ARGUMENTS_FILE_ON_TIRA
+    _URLS[_CONFIG_NAME_NYT_LEVEL1][_SPLIT_TYPE_TEST][_FILE_TYPE_ARGUMENTS] = _URL + _NYT_ARGUMENTS_FILE_ON_TIRA
+else:
+    # running locally
+    _URLS[_CONFIG_NAME_NYT][_SPLIT_TYPE_TEST][_FILE_TYPE_DOWNLOADER] = _NYT_DOWNLOADER_FILES
+    _URLS[_CONFIG_NAME_NYT_LEVEL1][_SPLIT_TYPE_TEST][_FILE_TYPE_DOWNLOADER] = _NYT_DOWNLOADER_FILES
+
+#########################
+# END OF: Data URLs #####
+#########################
+
+
+##########################
+# START OF: Features #####
+##########################
+
+_FEATURES_ARGUMENT_SETS = datasets.Features(
+    {
+        "Argument ID": datasets.Value("string"),
+        "Conclusion": datasets.Value("string"),
+        "Stance": datasets.Value("string"),
+        "Premise": datasets.Value("string"),
+        "Labels": datasets.Sequence(feature=datasets.Value("int32"))
+    }
+)
+
+_FEATURES_META_SETS = {
+    _CONFIG_NAME_META_A: datasets.Features(
+        {
+            "Argument ID": datasets.Value("string"),
+            "WA": datasets.Value("float64"),
+            "MACE-P": datasets.Value("float64"),
+            "stance_WA": datasets.Value("int32"),
+            "stance_WA_conf": datasets.Value("float64")
+        }
+    ),
+    _CONFIG_NAME_META_D: datasets.Features(
+        {
+            "Argument ID": datasets.Value("string"),
+            "URL": datasets.Value("string")
+        }
+    ),
+    _CONFIG_NAME_META_E: datasets.Features(
+        {
+            "Argument ID": datasets.Value("string"),
+            "URL": datasets.Value("string")
+        }
+    ),
+    _CONFIG_NAME_META_C: datasets.Features(
+        {
+            "Argument ID": datasets.Value("string"),
+            "Conclusion Chinese": datasets.Value("string"),
+            "Premise Chinese": datasets.Value("string"),
+            "URL": datasets.Value("string")
+        }
+    ),
+    _CONFIG_NAME_META_F: datasets.Features(
+        {
+            "Argument ID": datasets.Value("string"),
+            "Conclusion Farsi": datasets.Value("string"),
+            "Stance Farsi": datasets.Value("string"),
+            "Premise Farsi": datasets.Value("string"),
+            "Conclusion English": datasets.Value("string"),
+            "Stance English": datasets.Value("string"),
+            "Premise English": datasets.Value("string"),
+            "Source": datasets.Value("string"),
+            "Method": datasets.Value("string")
+        }
+    ),
+    _CONFIG_NAME_META_G: datasets.Features(
+        {
+            "Argument ID": datasets.Value("string"),
+            "URL": datasets.Value("string"),
+            "Internet Archive timestamp": datasets.Value("string")
+        }
+    ),
+    _CONFIG_NAME_VALUE_CATEGORIES: datasets.Features(
+        {
+            "Self-direction: thought": {
+                "Be creative": datasets.Sequence(feature=datasets.Value("string")),
+                "Be curious": datasets.Sequence(feature=datasets.Value("string")),
+                "Have freedom of thought": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Self-direction: action": {
+                "Be choosing own goals": datasets.Sequence(feature=datasets.Value("string")),
+                "Be independent": datasets.Sequence(feature=datasets.Value("string")),
+                "Have freedom of action": datasets.Sequence(feature=datasets.Value("string")),
+                "Have privacy": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Stimulation": {
+                "Have an exciting life": datasets.Sequence(feature=datasets.Value("string")),
+                "Have a varied life": datasets.Sequence(feature=datasets.Value("string")),
+                "Be daring": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Hedonism": {
+                "Have pleasure": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Achievement": {
+                "Be ambitious": datasets.Sequence(feature=datasets.Value("string")),
+                "Have success": datasets.Sequence(feature=datasets.Value("string")),
+                "Be capable": datasets.Sequence(feature=datasets.Value("string")),
+                "Be intellectual": datasets.Sequence(feature=datasets.Value("string")),
+                "Be courageous": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Power: dominance": {
+                "Have influence": datasets.Sequence(feature=datasets.Value("string")),
+                "Have the right to command": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Power: resources": {
+                "Have wealth": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Face": {
+                "Have social recognition": datasets.Sequence(feature=datasets.Value("string")),
+                "Have a good reputation": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Security: personal": {
+                "Have a sense of belonging": datasets.Sequence(feature=datasets.Value("string")),
+                "Have good health": datasets.Sequence(feature=datasets.Value("string")),
+                "Have no debts": datasets.Sequence(feature=datasets.Value("string")),
+                "Be neat and tidy": datasets.Sequence(feature=datasets.Value("string")),
+                "Have a comfortable life": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Security: societal": {
+                "Have a safe country": datasets.Sequence(feature=datasets.Value("string")),
+                "Have a stable society": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Tradition": {
+                "Be respecting traditions": datasets.Sequence(feature=datasets.Value("string")),
+                "Be holding religious faith": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Conformity: rules": {
+                "Be compliant": datasets.Sequence(feature=datasets.Value("string")),
+                "Be self-disciplined": datasets.Sequence(feature=datasets.Value("string")),
+                "Be behaving properly": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Conformity: interpersonal": {
+                "Be polite": datasets.Sequence(feature=datasets.Value("string")),
+                "Be honoring elders": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Humility": {
+                "Be humble": datasets.Sequence(feature=datasets.Value("string")),
+                "Have life accepted as is": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Benevolence: caring": {
+                "Be helpful": datasets.Sequence(feature=datasets.Value("string")),
+                "Be honest": datasets.Sequence(feature=datasets.Value("string")),
+                "Be forgiving": datasets.Sequence(feature=datasets.Value("string")),
+                "Have the own family secured": datasets.Sequence(feature=datasets.Value("string")),
+                "Be loving": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Benevolence: dependability": {
+                "Be responsible": datasets.Sequence(feature=datasets.Value("string")),
+                "Have loyalty towards friends": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Universalism: concern": {
+                "Have equality": datasets.Sequence(feature=datasets.Value("string")),
+                "Be just": datasets.Sequence(feature=datasets.Value("string")),
+                "Have a world at peace": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Universalism: nature": {
+                "Be protecting the environment": datasets.Sequence(feature=datasets.Value("string")),
+                "Have harmony with nature": datasets.Sequence(feature=datasets.Value("string")),
+                "Have a world of beauty": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Universalism: tolerance": {
+                "Be broadminded": datasets.Sequence(feature=datasets.Value("string")),
+                "Have the wisdom to accept others": datasets.Sequence(feature=datasets.Value("string"))
+            },
+            "Universalism: objectivity": {
+                "Be logical": datasets.Sequence(feature=datasets.Value("string")),
+                "Have an objective view": datasets.Sequence(feature=datasets.Value("string"))
+            }
+        }
+    )
+}
+
+########################
+# END OF: Features #####
+########################
+
+
+class ToucheValueEvalConfig(datasets.BuilderConfig):
+    """BuilderConfig for Touch\u00E923-ValueEval."""
+
+    def __init__(self, features, data_urls, citation=None, **kwargs):
+        """BuilderConfig for Touch\u00E923-ValueEval.
+
+        Args:
+            features: `list[string]`, list of the features that will appear in the
+                feature dict.
+            data_urls: `dict[string,dict[string,string]`, urls to download the dataset files from.
+            citation: `string`, citation for the data set.
+            **kwargs: keyword arguments forwarded to super.
+        """
+        # Version history:
+        # 0.0.2: Initial version.
+        super(ToucheValueEvalConfig, self).__init__(version=datasets.Version("0.0.2"), **kwargs)
+        self.features = features
+        self.data_urls = data_urls
+        self.citation = citation
+
+
+class ToucheValueEval(datasets.GeneratorBasedBuilder):
+    """The Touch\u00E923-ValueEval dataset."""
+
+    BUILDER_CONFIGS = [
+        ToucheValueEvalConfig(
+            name=_CONFIG_NAME_MAIN,
+            features=_FEATURES_ARGUMENT_SETS,
+            data_urls=_URLS[_CONFIG_NAME_MAIN],
+            description=_IBM_DESCRIPTION + '\n' + _COFE_DESCRIPTION + '\n' + _GROUP_DISCUSSION_IDEAS_DESCRIPTION + '\n' + _LEVEL2_DESCRIPTION,
+            citation=_IBM_CITATION + '\n' + _COFE_CITATION
+        ),
+        ToucheValueEvalConfig(
+            name=_CONFIG_NAME_MAIN_LEVEL1,
+            features=_FEATURES_ARGUMENT_SETS,
+            data_urls=_URLS[_CONFIG_NAME_MAIN_LEVEL1],
+            description=_IBM_DESCRIPTION + '\n' + _COFE_DESCRIPTION + '\n' + _GROUP_DISCUSSION_IDEAS_DESCRIPTION + '\n' + _LEVEL1_DESCRIPTION,
+            citation=_IBM_CITATION + '\n' + _COFE_CITATION
+        ),
+        ToucheValueEvalConfig(
+            name=_CONFIG_NAME_NAHJALBALAGHA,
+            features=_FEATURES_ARGUMENT_SETS,
+            data_urls=_URLS[_CONFIG_NAME_NAHJALBALAGHA],
+            description=_NAHJALBALAGHA_DESCRIPTION + '\n' + _LEVEL2_DESCRIPTION
+        ),
+        ToucheValueEvalConfig(
+            name=_CONFIG_NAME_NAHJALBALAGHA_LEVEL1,
+            features=_FEATURES_ARGUMENT_SETS,
+            data_urls=_URLS[_CONFIG_NAME_NAHJALBALAGHA],
+            description=_NAHJALBALAGHA_DESCRIPTION + '\n' + _LEVEL1_DESCRIPTION
+        ),
+        ToucheValueEvalConfig(
+            name=_CONFIG_NAME_NYT,
+            features=_FEATURES_ARGUMENT_SETS,
+            data_urls=_URLS[_CONFIG_NAME_NYT],
+            description=_NYT_DESCRIPTION + '\n' + _LEVEL2_DESCRIPTION
+        ),
+        ToucheValueEvalConfig(
+            name=_CONFIG_NAME_NYT_LEVEL1,
+            features=_FEATURES_ARGUMENT_SETS,
+            data_urls=_URLS[_CONFIG_NAME_NYT_LEVEL1],
+            description=_NYT_DESCRIPTION + '\n' + _LEVEL1_DESCRIPTION
+        ),
+        ToucheValueEvalConfig(
+            name=_CONFIG_NAME_ZHIHU,
+            features=_FEATURES_ARGUMENT_SETS,
+            data_urls=_URLS[_CONFIG_NAME_ZHIHU],
+            description=_ZHIHU_DESCRIPTION + '\n' + _LEVEL2_DESCRIPTION
+        ),
+        ToucheValueEvalConfig(
+            name=_CONFIG_NAME_ZHIHU_LEVEL1,
+            features=_FEATURES_ARGUMENT_SETS,
+            data_urls=_URLS[_CONFIG_NAME_ZHIHU_LEVEL1],
+            description=_ZHIHU_DESCRIPTION + '\n' + _LEVEL1_DESCRIPTION
+        ),
+        ToucheValueEvalConfig(
+            name=_CONFIG_NAME_META_A,
+            features=_FEATURES_META_SETS[_CONFIG_NAME_META_A],
+            data_urls=_URLS[_CONFIG_NAME_META_A],
+            description=_IBM_DESCRIPTION + '\n' + _IBM_META_DESCRIPTION,
+            citation=_IBM_CITATION
+        ),
+        ToucheValueEvalConfig(
+            name=_CONFIG_NAME_META_D,
+            features=_FEATURES_META_SETS[_CONFIG_NAME_META_D],
+            data_urls=_URLS[_CONFIG_NAME_META_D],
+            description=_GROUP_DISCUSSION_IDEAS_DESCRIPTION + '\n' + _GROUP_DISCUSSION_IDEAS_META_DESCRIPTION
+        ),
+        ToucheValueEvalConfig(
+            name=_CONFIG_NAME_META_E,
+            features=_FEATURES_META_SETS[_CONFIG_NAME_META_E],
+            data_urls=_URLS[_CONFIG_NAME_META_E],
+            description=_COFE_DESCRIPTION + '\n' + _COFE_META_DESCRIPTION,
+            citation=_COFE_CITATION
+        ),
+        ToucheValueEvalConfig(
+            name=_CONFIG_NAME_META_C,
+            features=_FEATURES_META_SETS[_CONFIG_NAME_META_C],
+            data_urls=_URLS[_CONFIG_NAME_META_C],
+            description=_ZHIHU_DESCRIPTION + '\n' + _ZHIHU_META_DESCRIPTION
+        ),
+        ToucheValueEvalConfig(
+            name=_CONFIG_NAME_META_F,
+            features=_FEATURES_META_SETS[_CONFIG_NAME_META_F],
+            data_urls=_URLS[_CONFIG_NAME_META_F],
+            description=_NAHJALBALAGHA_DESCRIPTION + '\n' + _NAHJALBALAGHA_META_DESCRIPTION
+        ),
+        ToucheValueEvalConfig(
+            name=_CONFIG_NAME_META_G,
+            features=_FEATURES_META_SETS[_CONFIG_NAME_META_G],
+            data_urls=_URLS[_CONFIG_NAME_META_G],
+            description=_NYT_DESCRIPTION + '\n' + _NYT_META_DESCRIPTION
+        ),
+        ToucheValueEvalConfig(
+            name=_CONFIG_NAME_VALUE_CATEGORIES,
+            features=_FEATURES_META_SETS[_CONFIG_NAME_VALUE_CATEGORIES],
+            data_urls=_URLS[_CONFIG_NAME_VALUE_CATEGORIES],
+            description=_CATEGORIES_JSON_DESCRIPTION
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = _CONFIG_NAME_MAIN
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION + self.config.description,
+            features=self.config.features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=(self.config.citation + '\n' if self.config.citation is not None else '') + _CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls = self.config.data_urls
+        file_dict = dl_manager.download_and_extract(urls)
+
+        if self.config.name == _CONFIG_NAME_MAIN or self.config.name == _CONFIG_NAME_MAIN_LEVEL1:
+            splits = [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "filepaths": file_dict[_SPLIT_TYPE_TRAIN],
+                        "split": _SPLIT_TYPE_TRAIN
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.VALIDATION,
+                    gen_kwargs={
+                        "filepaths": file_dict[_SPLIT_TYPE_VAL],
+                        "split": _SPLIT_TYPE_VAL
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    gen_kwargs={
+                        "filepaths": file_dict[_SPLIT_TYPE_TEST],
+                        "split": _SPLIT_TYPE_TEST
+                    },
+                ),
+            ]
+        elif self.config.name in [_CONFIG_NAME_ZHIHU, _CONFIG_NAME_ZHIHU_LEVEL1]:
+            splits = [
+                datasets.SplitGenerator(
+                    name=datasets.Split.VALIDATION,
+                    gen_kwargs={
+                        "filepaths": file_dict[_SPLIT_TYPE_VAL],
+                        "split": _SPLIT_TYPE_VAL
+                    },
+                ),
+            ]
+        elif self.config.name in [_CONFIG_NAME_NYT, _CONFIG_NAME_NYT_LEVEL1]:
+            splits = [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    gen_kwargs={
+                        "filepaths": file_dict[_SPLIT_TYPE_TEST],
+                        "split": _SPLIT_TYPE_TEST
+                    },
+                ),
+            ]
+        elif self.config.name in [_CONFIG_NAME_NAHJALBALAGHA, _CONFIG_NAME_NAHJALBALAGHA_LEVEL1]:
+            splits = [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    gen_kwargs={
+                        "filepaths": file_dict[_SPLIT_TYPE_TEST],
+                        "split": _SPLIT_TYPE_TEST
+                    },
+                ),
+            ]
+        else:
+            splits = [
+                datasets.SplitGenerator(
+                    name=_SPLIT_META,
+                    gen_kwargs={
+                        "filepaths": file_dict[_SPLIT_TYPE_META],
+                        "split": _SPLIT_TYPE_META
+                    },
+                ),
+            ]
+        return splits
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, filepaths, split):
+        file_types = filepaths.keys()
+
+        if self.config.name in [_CONFIG_NAME_NYT, _CONFIG_NAME_NYT_LEVEL1] and _FILE_TYPE_DOWNLOADER in file_types:
+            # running locally => download nyt arguments
+            downloader_paths = filepaths[_FILE_TYPE_DOWNLOADER]
+
+            directory = os.path.dirname(downloader_paths['downloader'])
+            arguments_file = os.path.join(directory, _NYT_ARGUMENTS_FILE_LOCAL)
+            if not os.path.exists(arguments_file):
+                subprocess.check_call(f"pip3 install -r {downloader_paths['requirements']}", shell=True, stdout=sys.stdout,
+                                      stderr=subprocess.STDOUT)
+                subprocess.check_call(f"spacy download en_core_web_sm", shell=True, stdout=sys.stdout,
+                                      stderr=subprocess.STDOUT)
+                subprocess.check_call(
+                    f"python3 {downloader_paths['downloader']} --input-file {downloader_paths['input-file']} --output-file {arguments_file}",
+                    shell=True, stdout=sys.stdout, stderr=subprocess.STDOUT)
+            # extract checksum
+            with open(downloader_paths['checksum'], mode='r', encoding='utf-8') as f:
+                checksum = f.readline().split('  ')[0]
+            subprocess.check_call(f"echo \"{checksum} {arguments_file}\" | sha256sum --check", shell=True,
+                                  stdout=sys.stdout, stderr=subprocess.STDOUT)
+
+            filepaths[_FILE_TYPE_ARGUMENTS] = arguments_file
+
+        if _FILE_TYPE_ARGUMENTS in file_types:
+            # argument data
+            with open(filepaths[_FILE_TYPE_ARGUMENTS], encoding='utf-8') as f:
+                dataframe_arguments = pd.read_csv(f, sep='\t', header=0)
+
+            if _FILE_TYPE_LABELS not in file_types:
+                label_names = []
+            else:
+                with open(filepaths[_FILE_TYPE_LABELS], encoding='utf-8') as f:
+                    dataframe_labels = pd.read_csv(f, sep='\t', header=0)
+
+                label_names = [x for x in dataframe_labels.columns if x != "Argument ID"]
+                dataframe_arguments = dataframe_arguments.join(
+                    dataframe_labels.set_index('Argument ID'), on='Argument ID', how='inner'
+                )
+
+            for key, row in dataframe_arguments.iterrows():
+                yield key, {
+                    "Argument ID": row["Argument ID"],
+                    "Conclusion": row["Conclusion"],
+                    "Stance": row["Stance"],
+                    "Premise": row["Premise"],
+                    "Labels": [int(row[x]) for x in label_names],
+                }
+        elif _FILE_TYPE_META in file_types:
+            # meta data
+            with open(filepaths[_FILE_TYPE_META], encoding='utf-8') as f:
+                dataframe_meta = pd.read_csv(f, sep='\t', header=0)
+
+            for key, row in dataframe_meta.iterrows():
+                yield key, {str(column): row[str(column)] for column in row.keys()}
+        else:
+            # json data
+            with open(filepaths[_FILE_TYPE_JSON], encoding='utf-8') as f:
+                value_categories = json.load(f)
+
+            yield 0, value_categories

data/validationzhihu-00000-of-00001.tsv

@@ -1,101 +0,0 @@
-Argument ID	Conclusion	Stance	Premise	Labels
-C26001	We should abolish the 996 overtime system	in favor of	China's 996 overtime system is very inefficient in enhancing your ability to make money. If you rely on 996 to make money, you are essentially making money by working hard, selling your body.	[0,0,0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0]
-C26002	We should abolish the 996 overtime system	in favor of	China's 996 overtime system leaves you with no room to learn and improve, forever trapped in a "rat trap".	[0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0]
-C26003	We should abolish the 996 overtime system	against	For the poor people, if they can go to the Internet factory, China's 996 overtime system is a blessing, twelve hours a day, six days a week, can also rest a day, quite good.	[0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0]
-C26004	We should abolish the 996 overtime system	in favor of	China's 996 overtime system violates labor laws.	[0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0]
-C26005	We should abolish the 996 overtime system	against	Corporate management seeks to maximize profits, and China's 996 overtime system can reduce operating costs, especially labor costs.	[0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0]
-C26006	We should give up developing electric vehicles	against	The electric car is driven by an electric motor and has a direct maximum torque at start-up, which is faster than the fuel car power section.	[0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
-C26007	We should give up developing electric vehicles	against	The intelligence of electric cars is much higher than that of fuel cars.	[0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
-C26008	We should give up developing electric vehicles	against	Electric cars are much cheaper to use than fuel cars over the life cycle of a car.	[0,0,0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0]
-C26009	We should give up developing electric vehicles	in favor of	The development of electric vehicle batteries is a highly polluting industry. Even the batteries will bring very serious pollution if they cannot be recycled.	[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0]
-C26010	We should give up developing electric vehicles	in favor of	Market orientation is difficult. In the absence of subsidies, no license restrictions and other policies, whether the sales of pure electric vehicles can still grow steadily is questionable.	[0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1]
-C26011	We should give up developing electric vehicles	in favor of	Power battery energy density is relatively low and stability is not high, the battery industry needs to break through the technical bottleneck or find cost-effective alternative products.	[0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
-C26012	We should give up developing electric vehicles	in favor of	The number of charging infrastructure construction is not enough.	[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
-C26013	We should give up developing electric vehicles	in favor of	Low user confidence, low acceptance of new things, even from earlier scandalous events in the electric vehicles industry.	[0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1]
-C26014	We should ban the trading of virtual currencies.	in favor of	Virtual currency is a money laundering channel for criminals.	[0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0]
-C26015	We should ban the trading of virtual currencies.	in favor of	Cracking down on virtual currencies is not only to ensure the smooth advancement of carbon peak and carbon neutrality, but also to protect the country's financial order.	[0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,1,0,0]
-C26016	We should ban the trading of virtual currencies.	in favor of	Virtual currency is not protected by contract law and property law in China.	[0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0]
-C26017	We should ban the trading of virtual currencies.	in favor of	Digital currency not only cannot create foreign exchange, but also causes foreign exchange outflow	[0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0]
-C26018	We should ban the trading of virtual currencies.	in favor of	Virtual currency-related business activities are illegal financial activities, and the provision of services by overseas virtual currency exchanges to Chinese residents through the Internet is also illegal financial activities.	[0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0]
-C26019	We should ban the trading of virtual currencies.	in favor of	Virtual currency creation does not provide commodities with corresponding value to the market.	[0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
-C26020	We should ban the trading of virtual currencies.	against	Virtual currencies have changed the way of commercial realization. The birth of virtual currency, the token system, is designed to overturn the current business logic.	[1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
-C26021	We should ban the trading of virtual currencies.	against	Cryptocurrency can change the way of value transmission, that is, it can allow the uncontrolled flow of funds around the world.	[0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1]
-C26022	We should ban the trading of virtual currencies.	against	The organizational structure brought about by the blockchain distributed technology replaces what a beautiful society this is. There is no corruption and it discards all the disadvantages of centralization.	[0,0,0,0,1,0,1,0,1,1,0,0,0,0,0,0,0,0,0,0]
-C26023	We should ban the trading of virtual currencies.	against	Security, virtual currency is encrypted with high aspect ratio data, after the sale is created, it is always unlikely to carry out changes and forgeries.	[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
-C26024	We should ban the trading of virtual currencies.	against	The total production is controllable and the virtual currency prevents hyperinflation.	[0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0]
-C26025	We should ban the trading of virtual currencies.	against	Portable, because it is a virtual currency, so it is highly portable when it is bought and sold.	[0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
-C26026	We should ban the trading of virtual currencies.	against	Virtual currency improves liquidity and improves the efficiency of economic and social commodity circulation.	[0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0]
-C26027	We should ban the trading of virtual currencies.	against	Every transaction of virtual currency generated in the blockchain technology Internet cannot be forged, and it will not be manipulated by individuals, so it has a good anti-counterfeiting feature.	[0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1]
-C26028	We should ban the trading of virtual currencies.	against	The trading of virtual currency is secretly named, so as to ensure the privacy protection of his own information content and data information, prevent the leakage of his own data, and improve the safety factor of the system software.	[0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
-C26029	We should protect our privacy in the Internet age.	in favor of	In the era of IoT sharing economy, because of linking people and people, people and things, and things and things, the probability of the system being exploited and hacked is also increased.	[0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0]
-C26030	We should protect our privacy in the Internet age.	in favor of	The leaked personal information will be defrauded by fraud gangs to gain trust and carry out fraudulent activities.	[0,1,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0]
-C26031	We should protect our privacy in the Internet age.	in favor of	Most people have to rely on centralized information distribution and dissemination platforms to publish information. It is easy to control the output and control of ideology, social ideas and hotspots.	[0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0]
-C26032	We should protect our privacy in the Internet age.	in favor of	Extremely serious information asymmetry. It is difficult for individuals to know what information is being collected about them, who is collecting it, and what it is being used for.	[0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0]
-C26033	We should protect our privacy in the Internet age.	in favor of	You can barely recover privacy. It's hard to imagine what companies do with personal information, including who they actually sell it to.	[0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0]
-C26034	We should protect our privacy in the Internet age.	against	Recording precise data of individuals can improve individual lives; recording huge data of groups can optimize resource allocation.	[0,0,0,0,1,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0]
-C26035	We should protect our privacy in the Internet age.	in favor of	In the event of a cloud data loss or data breach, the data cannot be recovered.	[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
-C26036	We should protect our privacy in the Internet age.	in favor of	Attackers can use their own security-aware enterprise users as a breakthrough to attack from the short end of the barrel, making other enterprise users of the same cloud platform equally dangerous.	[0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0]
-C26037	We should protect our privacy in the Internet age.	against	The data provided by privacy can be used to analyze user preferences and needs, and can quickly learn about the shortcomings of the product, correspondingly update more business models, and help achieve business improvement. Help companies gain greater competitiveness.	[0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
-C26038	We should protect our privacy in the Internet age.	against	If the laws and regulations on privacy protection in one region or country are too stringent, it is likely to lead to the transfer of capital to another region or country.	[0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0]
-C26039	We should restrict minors from playing online games.	in favor of	Many teenagers in China use electronic devices to play games as the only entertainment after study. At the same time, the same kind of people in Europe and the United States choose more diverse ways.	[0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0]
-C26040	We should restrict minors from playing online games.	against	Children's addiction to games may not be a problem of games in essence, but a comprehensive problem of family education, children's habits, hobby training and so on.	[0,0,0,0,1,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0]
-C26041	We should restrict minors from playing online games.	against	Ban them from playing games and they may indulge in short videos on Douyin.	[0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
-C26042	We should restrict minors from playing online games.	against	Instead of banning games, it might be better to increase young people's awareness of life and society, and to promote self-awareness and active thinking among students.	[1,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0]
-C26043	We should restrict minors from playing online games.	in favor of	Students who do not learn well are more likely to indulge in games. They cannot find a sense of accomplishment in real life.	[0,0,0,0,1,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0]
-C26044	We should restrict minors from playing online games.	against	Rather than restricting minors to play games, parents should set a good example and spend more time with their children.	[0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0]
-C26045	We should restrict minors from playing online games.	in favor of	Long-term addiction to online games can change the structure of a child's brain. Imagination, thinking and integration skills are not trained.	[1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
-C26046	We should restrict minors from playing online games.	against	Putting all the blame on the game, demonizing the game, and putting the blame on society can ease parents' anxiety, but it does not help at all.	[0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1]
-C26047	We should restrict minors from playing online games.	against	Ban games for students and they will not go to play basketball, do sports or learn, but will only turn to more vulgar vulgarization more harmful forms of entertainment.	[1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
-C26048	We should open up three-child policy to encourage childbirth.	against	To solve the fertility problem in the long term, we need to start at the source: for example, giving young people less pressure to work, regulating and stabilizing housing prices and so on.	[0,0,0,0,0,0,0,0,1,1,0,0,0,0,1,0,0,0,1,0]
-C26049	We should open up three-child policy to encourage childbirth.	against	What people want is the right and freedom to be able to plan their own children.	[0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0]
-C26050	We should open up three-child policy to encourage childbirth.	against	Other measures such as subsidizing childbirth, reducing the cost of health care and education for the population, and protecting women more from the law and the workplace are more imminent.	[0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0,0,1]
-C26051	We should open up three-child policy to encourage childbirth.	against	No matter what the social policy is, the more the society develops, the more free people are, and the more independent women are. The decline in fertility is an inevitable trend.	[0,1,0,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,0]
-C26052	We should open up three-child policy to encourage childbirth.	in favor of	The number of births is too small, which affects the overall economic growth.	[0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0]
-C26053	We should open up three-child policy to encourage childbirth.	against	The people at the Health Planning Commission thought there would be a population explosion after opening up childbirth, but in reality people don't want to have children, whether you restrain them or not.	[0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0]
-C26054	We should open up three-child policy to encourage childbirth.	in favor of	China's population structure has gradually become aging and has become a burden for economic growth.	[0,0,0,0,1,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0]
-C26055	We should open up three-child policy to encourage childbirth.	in favor of	Class entrenchment and the fading desire of youth to continue to struggle, youth believe that no amount of effort can keep up with the growth of housing prices	[0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0]
-C26056	We should prohibit capital monopoly.	in favor of	Capital monopoly hinders the efficient allocation of resources and causes waste of resources.	[0,0,0,0,1,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0]
-C26057	We should prohibit capital monopoly.	in favor of	Capital monopolies distort market prices and undermine fair competition in the market.	[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0]
-C26058	We should prohibit capital monopoly.	in favor of	Capital monopolies hinder technological progress and harm consumers' interests.	[0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0]
-C26059	We should prohibit capital monopoly.	in favor of	Capital monopoly raises the barrier of entry for other enterprises and hinders the high-quality development of the national economy.	[0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0]
-C26060	We should prohibit capital monopoly.	in favor of	The purpose of anti-monopoly is not to combat a few monopolies, but to oppose the abuse of monopoly.	[0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0]
-C26061	We should prohibit capital monopoly.	in favor of	Anti-capital monopoly prevents operators from abusing their dominant market position.	[0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,0,0,0]
-C26062	We should prohibit capital monopoly.	against	Monopoly profits are the driving force behind technological progress in areas that require significant investment in research and development.	[0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0]
-C26063	We should prohibit capital monopoly.	against	Monopolies can sometimes protect the public interest in infrastructure areas such as energy and transportation, which are vital to the livelihood of the nation.	[0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0]
-C26064	We should prohibit capital monopoly.	in favor of	The greatest harm of monopoly lies in the destruction of competition, so that businesses no longer need to care about the feelings of consumers.	[0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0]
-C26065	We should prevent the disorderly expansion of capital.	in favor of	Capital combined with Internet technology, using asymmetric advantages such uncontrolled expansion, snatching the rice bowls of small businessmen and vendors, has constituted a violation of the basic ethics of society.	[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0]
-C26066	We should prevent the disorderly expansion of capital.	in favor of	Behind each hawker, there is a family at the grassroots of society to support, so that these vendors survive, to prevent the structural division of society between rich and poor.	[0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0]
-C26067	We should prevent the disorderly expansion of capital.	in favor of	Capital cannot be allowed to take advantage of the power of science and technology to form a monopoly in this particular field, allowing millions of hawkers to have their rice bowls taken away.	[0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0]
-C26068	We should prevent the disorderly expansion of capital.	in favor of	The means by which the giants seized the market was essentially by selling below cost, which is unfair competition, and then using their monopoly position to raise prices, which is divorced from the intent of a market economy.	[0,0,0,0,0,0,0,0,1,1,0,1,0,0,0,0,1,0,0,1]
-C26069	We should crack down on unreasonably high incomes.	in favor of	Strengthen the regulation and adjustment of high income, protect legitimate income according to law, reasonably adjust excessive income, and encourage high-income people and enterprises to give more back to society.	[0,0,0,0,1,0,0,0,0,0,0,1,0,1,1,0,0,0,0,0]
-C26070	We should crack down on unreasonably high incomes.	against	Individuals cannot be sure that they can continue to have high incomes and that their industry can continue to guarantee high incomes for employees.	[0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1]
-C26071	We should crack down on unreasonably high incomes.	against	If the key to an individual's standard of living does not lie in income, then it is useless to simply regulate income.	[0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0]
-C26072	We should crack down on unreasonably high incomes.	in favor of	Rich people take advantage of the assets in their hands to harvest the wealth of the general public. Transfer the gold to themselves and leave the bubble to others.	[0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,1,0,0,0]
-C26073	We should crack down on unreasonably high incomes.	in favor of	The rich use the wealth in their hands to build a network of interests to continuously strengthen and consolidate their own interests. Blocking others' class upward path.	[0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0]
-C26074	We should crack down on unreasonably high incomes.	in favor of	Regulate excessive income, consistent with common prosperity. Common prosperity is the prosperity of all the people, the people's material and spiritual life are rich, to promote common prosperity in stages.	[0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0]
-C26075	We should crack down on unreasonably high incomes.	in favor of	The implementation of property taxes, taxes on the rich, capital gains taxes, asset transfer taxes, etc. The fundamental factor leading to the disparity between the rich and the poor in the past decades is not the pay gap, but the gap brought about by the growth of capital investment.	[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1]
-C26076	We should crack down on unreasonably high incomes.	against	It is more important to raise the income of the lower class in the distribution system and to lower the cost of living of the lower and middle class than to fight against high income.	[0,0,0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,0,0,1]
-C26077	We should crack down on unreasonably high incomes.	against	It is difficult to tax high income earners. After all, high income earners have many sources of income, tax avoidance means, really can not also immigrate. The ordinary middle class has a single source of income, which is basically wages, and is easily taxed.	[0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,1]
-C26078	We should ease the education involution.	in favor of	A society's value of education should not remain "score-only" and "testing-only".	[1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1]
-C26079	We should ease the education involution.	against	With a still large graduate base, increasingly high thresholds can only be passed by the top achievers.	[0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1]
-C26080	We should ease the education involution.	in favor of	Parents play an important role in the education in-volume, and parents with insufficient determination can easily be held hostage by the general environment and bring anxiety to their children, causing a vicious cycle.	[0,0,0,0,1,0,0,0,1,0,0,0,0,0,1,1,0,0,0,0]
-C26081	We should ease the education involution.	in favor of	The most fundamental thing is to improve the basic educational literacy of parents and advocate the educational concept of "how to be a good person is more important than success and happiness is more important than success".	[0,0,0,0,1,0,0,0,1,1,0,0,1,0,1,0,0,0,0,0]
-C26082	We should ease the education involution.	in favor of	Parents' overwhelming fear-dominated anxiety is the greatest enemy of education; the intent of education should be to make a person become a better version of himself.	[1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
-C26083	We should ease the education involution.	in favor of	The overall test-taking ability of students has improved, but the top stream universities and other quality educational resources have not increased proportionally.	[0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
-C26084	We should vigorously develop the countryside.	in favor of	The gap between rural and urban areas is getting bigger and bigger, and the result is that the countryside is deserted, a lot of land is barren, and China's arable land is decreasing.	[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0]
-C26085	We should vigorously develop the countryside.	in favor of	The gap between urban and rural areas must be narrowed, or social conflicts will intensify.	[0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0]
-C26086	We should vigorously develop the countryside.	against	The city is full of opportunities, it gives outworkers prosperity and convenience, and everyone can live in the city with their own power, and even gradually gain a foothold in the city.	[0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
-C26087	We should vigorously develop the countryside.	in favor of	Unemployment and urbanization when combined are slums and instability, so the rural areas need to be allowed to absorb the unemployed.	[0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,1]
-C26088	We should vigorously develop the countryside.	against	The future of the rural market will certainly be prosperous, but at present it is barren, and the risk of investing in business is still relatively high. This largely limits young people's footsteps.	[0,0,0,0,1,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0]
-C26089	We should vigorously develop the countryside.	in favor of	In this field of food we can not be subject to others, even if imported food is cheaper, we can not rely on imports, but to vigorously develop our own level of agriculturalization.	[0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0]
-C26090	We should vigorously develop the countryside.	in favor of	There is a lack of employment opportunities in rural areas, as well as inadequate education, medical care and infrastructure. Therefore, we must vigorously develop the rural revitalization strategy and related industries, so that young people can return to rural areas.	[0,0,0,0,1,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0]
-C26091	Carbon emissions trading should be limited.	against	Since China's reform and opening up, its economy has developed rapidly, and Western countries have taken advantage of the warming climate to limit the issue of carbon emission rights in order to delay China's development.	[0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0]
-C26092	Carbon emissions trading should be limited.	against	The main purpose of the World Climate Conference in Copenhagen was to curb the development of late-developing countries, especially China, and to limit the carbon emission rights of developing countries.	[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0]
-C26093	Carbon emissions trading should be limited.	in favor of	Climate change is a global issue facing mankind, and with carbon dioxide emissions from all countries, greenhouse gases are surging, posing a threat to life systems.	[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0]
-C26094	Carbon emissions trading should be limited.	in favor of	China's processing capacity is increasing, while carbon emissions are accelerating. The development of a low-carbon economy and the reshaping of the energy system have important security implications.	[0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,1]
-C26095	Carbon emissions trading should be limited.	against	No one can stop global warming, which is inherently part of the Earth's geological cycle. That's why topics such as reducing CO2 emissions are a false proposition.	[0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1]
-C26096	Carbon emissions trading should be limited.	in favor of	To reduce carbon emissions, first of all, the country will close many heavy polluting enterprises.	[0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0]
-C26097	Carbon emissions trading should be limited.	in favor of	The national reduction of carbon emissions will pull the transformation of the entire national energy structure.	[0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,1]
-C26098	Carbon emissions trading should be limited.	against	Setting tough standards on carbon emissions can suppress industrial upgrading in developing countries and prevent them from challenging the monopoly advantage of EU countries in high-end industries.	[0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0]
-C26099	Carbon emissions trading should be limited.	in favor of	Promoting global energy conservation and emission reduction can slow down the trend of China's low-end industries moving to third world countries, thus strengthening its position as a major manufacturing country.	[0,0,0,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0]
-C26100	Carbon emissions trading should be limited.	in favor of	China's active participation in carbon emissions trading will help to enhance the country's international image.	[0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0]