Update README.md

README.md

@@ -31,18 +31,12 @@ data = datasets.load_dataset('SLPL/syntran-fa', split="train")
   - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
   - [Languages](#languages)
 - [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
 - [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
   - [Source Data](#source-data)
   - [Annotations](#annotations)
   - [Personal and Sensitive Information](#personal-and-sensitive-information)
 - [Considerations for Using the Data](#considerations-for-using-the-data)
   - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
 - [Additional Information](#additional-information)
   - [Dataset Curators](#dataset-curators)
   - [Licensing Information](#licensing-information)
@@ -60,10 +54,7 @@ data = datasets.load_dataset('SLPL/syntran-fa', split="train")
 
 Generating fluent responses has always been challenging for the question-answering task, especially in low-resource languages like Farsi. In recent years there were some efforts for enhancing the size of datasets in Farsi. Syntran-fa is a question-answering dataset that accumulates the former Farsi QA dataset's short answers and proposes a complete fluent answer for each pair of (question, short_answer).
 
-This dataset contains nearly 50,000 indices of questions and answers. The dataset that has been used as our sources were as follows:
-+ [PersianQA](https://github.com/sajjjadayobi/PersianQA)
-+ [PersianQuAD](https://ieeexplore.ieee.org/document/9729745)
-+ [PQuAD](https://arxiv.org/abs/2202.06219)
+This dataset contains nearly 50,000 indices of questions and answers. The dataset that has been used as our sources are in [Source Data section](#source-data).
 
 The main idea for this dataset comes from [Fluent Response Generation for Conversational Question Answering](https://aclanthology.org/2020.acl-main.19.pdf) where they used a "parser + syntactic rules" module to make different fluent answers from a pair of question and a short answer using a parser and some syntactic rules. In this project, we used [stanza](https://stanfordnlp.github.io/stanza/) as our parser to parse the question and generate a response according to it using the short (1-2 word) answers. One can continue this project by generating different permutations of the sentence's parts (and thus providing more than one sentence for an answer) or training a seq2seq model which does what we do with our rule-based system (by defining a new text-to-text task).
 
@@ -100,19 +91,16 @@ Currently, the dataset just provided the `train` split. There would be a `test`
 
 ## Dataset Creation
 
-[More Information Needed]
-
-### Curation Rationale
-
-[More Information Needed]
+We extract all short answer (1-2 words as answer) entries of all open source QA datasets in Farsi and used some rules featuring the question parse tree to make long (fluent) answers.
 
 ### Source Data
+The source datasets that we used are as follows:
 
-#### Initial Data Collection and Normalization
-
-[More Information Needed]
++ [PersianQA](https://github.com/sajjjadayobi/PersianQA)
++ [PersianQuAD](https://ieeexplore.ieee.org/document/9729745)
++ [PQuAD](https://arxiv.org/abs/2202.06219)
 
-#### Who are the source language producers?
+#### Initial Data Collection and Normalization
 
 [More Information Needed]
 
@@ -128,19 +116,13 @@ Currently, the dataset just provided the `train` split. There would be a `test`
 
 ### Personal and Sensitive Information
 
-[More Information Needed]
+The dataset is completely a subset of open source known datasets so all information in it is already there on the internet as a open-source dataset. By the way, we do not take responsibility for any of that.
 
 ## Considerations for Using the Data
 
-### Social Impact of Dataset
-
 [More Information Needed]
 
-### Discussion of Biases
-
-[More Information Needed]
-
-### Other Known Limitations
+### Social Impact of Dataset
 
 [More Information Needed]
 
@@ -148,7 +130,7 @@ Currently, the dataset just provided the `train` split. There would be a `test`
 
 ### Dataset Curators
 
-[More Information Needed]
+The dataset is gathered together completely in the Asr Gooyesh Pardaz company's summer internship under the supervision of Soroush Gooran, Prof. Hossein Sameti, and the mentorship of Sadra Sabouri. This project was Farhan Farsi's first internship project. 
 
 ### Licensing Information