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README.md

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----
-license: cc-by-sa-4.0
-license_name: other
-license_link: LICENSE
----
+## Table of Contents
+- [Dataset Card Creation Guide](#dataset-card-creation-guide)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+  - [Additional Information](#additional-information)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Repository:** [https://github.com/Orange-OpenSource/CoQAR/]()
+- **Paper:** [https://arxiv.org/abs/2207.03240]()
+- **Point of Contact:** <quentin.brabant@orange.com>, <gwenole.lecorve@orange.com>, <linamaria.rojasbarahona@orange.com>
+
+### Dataset Summary
+
+CoQAR is a corpus containing 4.5K conversations from the open-source dataset [Conversational Question-Answering dataset CoQA](https://stanfordnlp.github.io/coqa/), for a total of 53K follow-up question-answer pairs. 
+In CoQAR each original question was manually annotated with at least 2 at most 3 out-of-context rewritings.
+COQAR can be used for (at least) three NLP tasks: question paraphrasing, question rewriting and conversational question answering.
+
+We annotated each original question of CoQA with at least 2 at most 3 out-of-context rewritings. 
+
+![image](https://user-images.githubusercontent.com/52821991/165952155-822ce743-791d-46c8-8705-0937a69df933.png)
+
+
+### Languages
+
+English.
+
+## Dataset Structure
+
+The dataset is composed of several conversations. Each row correspond to one question of one conversation. The fields are the following:
+
+- conversation_id
+- turn_id: first question has turn id 0, second question has turn id 1, etc.
+- original_question: string
+- question_paraphrases : list of decontextualized rewrittings of the original question,
+- answer: string, answer to the question,
+- answer_span_start: start of the answer span (char number in the story),
+- answer_span_end: end of the answer span (char number in the story),
+- answer_span_text: string, excerpt of the story from answer_span_start to answer_span_end,
+- conversation_history: list of strings corresponding to previous (original) questions and answers,
+- file_name
+- story
+- name
+
+
+## Additional Information
+
+### Licensing Information
+
+The annotations are published under the licence CC-BY-SA 4.0.
+The original content of the dataset CoQA is under the distinct licences described below.
+
+The corpus CoQA contains passages from seven domains, which are public under the following licenses:
+ - Literature and Wikipedia passages are shared under CC BY-SA 4.0 license. 
+ - Children's stories are collected from MCTest which comes with MSR-LA license. 
+ - Middle/High school exam passages are collected from RACE which comes with its own license. 
+ - News passages are collected from the DeepMind CNN dataset which comes with Apache license (see [K. M. Hermann, T. Kočiský and E. Grefenstette, L. Espeholt, W. Kay, M. Suleyman, P. Blunsom, Teaching Machines to Read and Comprehend. Advances in Neural Information Processing Systems (NIPS), 2015](http://arxiv.org/abs/1506.03340)).
+
+
+### Citation Information
+
+```
+@inproceedings{brabant-etal-2022-coqar,
+    title = "{C}o{QAR}: Question Rewriting on {C}o{QA}",
+    author = "Brabant, Quentin  and
+      Lecorv{\'e}, Gw{\'e}nol{\'e}  and
+      Rojas Barahona, Lina M.",
+    booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
+    month = jun,
+    year = "2022",
+    address = "Marseille, France",
+    publisher = "European Language Resources Association",
+    url = "https://aclanthology.org/2022.lrec-1.13",
+    pages = "119--126"
+}
+```