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A dataset and baselines for sequential open-domain question answering

2018-10-01EMNLP 2018Unverified0· sign in to hype

Ahmed Elgohary, Chen Zhao, Jordan Boyd-Graber

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Abstract

Previous work on question-answering systems mainly focuses on answering individual questions, assuming they are independent and devoid of context. Instead, we investigate sequential question answering, asking multiple related questions. We present QBLink, a new dataset of fully human-authored questions. We extend existing strong question answering frameworks to include previous questions to improve the overall question-answering accuracy in open-domain question answering. The dataset is publicly available at http://sequential.qanta.org.

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