| ## 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. | |
|  | |
| ### 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: string providing context for the conversation, from which the answers can be deduced | |
| - 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" | |
| } | |
| ``` |