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HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
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HotpotQA Homepage HotpotQA Menu Blog Explorer HotpotQA A Dataset for Diverse, Explainable Multi-hop Question Answering What is HotpotQA? HotpotQA is a question answering dataset featuring natural, multi-hop questions, with strong supervision for supporting facts to enable more explainable question answering systems. It is collected by a team of NLP researchers at Carnegie Mellon University , Stanford University , and Université de Montréal . For more details about HotpotQA, please refer to our EMNLP 2018 paper: (Yang, Qi, Zhang, et al. 2018) If you work on open-domain multi-hop question answering, you might also be interested in a new dataset one of our authors (Peng Qi) published more recently, BeerQA , which features open-domain questions that might require varying hops of reasoning to answer, and which HotpotQA is made part of. Getting started HotpotQA is distributed under a CC BY-SA 4.0 License . The training and development sets can be downl...
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