Datasets:
ArXiv:
License:
| license: apache-2.0 | |
| # Dataset Card for FeedbackQA | |
| [π Read](https://arxiv.org/pdf/2204.03025.pdf)<br> | |
| [πΎ Code](https://github.com/McGill-NLP/feedbackqa)<br> | |
| [π Webpage](https://mcgill-nlp.github.io/feedbackqa/)<br> | |
| [π» Demo](http://206.12.100.48:8080/)<br> | |
| [π€ Huggingface Dataset](https://huggingface.co/datasets/McGill-NLP/feedbackQA)<br> | |
| [π¬ Discussions](https://github.com/McGill-NLP/feedbackqa/discussions) | |
| ## Dataset Description | |
| - **Homepage: https://mcgill-nlp.github.io/feedbackqa-data/** | |
| - **Repository: https://github.com/McGill-NLP/feedbackqa-data/** | |
| - **Paper:** | |
| - **Leaderboard:** | |
| - **Tasks: Question Answering** | |
| ### Dataset Summary | |
| FeedbackQA is a retrieval-based QA dataset that contains interactive feedback from users. | |
| It has two parts: the first part contains a conventional RQA dataset, | |
| whilst this repo contains the second part, which contains feedback(ratings and natural language explanations) for QA pairs. | |
| ### Languages | |
| English | |
| ## Dataset Creation | |
| For each question-answer pair, we collected multiple feedback, each of which consists of a rating, selected | |
| from excellent, good, could be improved, bad, and a natural language explanation | |
| elaborating on the strengths and/or weaknesses of the answer. | |
| #### Initial Data Collection and Normalization | |
| We scraped Covid-19-related content from official websites. | |
| ### Annotations | |
| #### Who are the annotators? | |
| Crowd-workers | |
| ### Licensing Information | |
| Apache 2.0 | |
| ### Contributions | |
| [McGill-NLP](https://github.com/McGill-NLP) | |