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