CANARD: A dataset for Question-in-Context Rewriting

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CANARD_Release.zip (3.11 MB)
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Date

2019-11-03

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Ahmed Elgohary, Denis Peskov, and Jordan Boyd-Graber. Can You Unpack That? Learning to Rewrite Questions-in-Context. Empirical Methods in Natural Language Processing, 2019.

Abstract

In conversational question answering multiple questions in an information-seeking dialogs which requires models to link questions together to resolve the conversational dependencies between them: each question needs to be under- stood in the conversation context. For example, the question “What was he like in that episode?” cannot be understood without knowing what “he” and “that episode” refer to, which can be resolved using the conversation context. CANARD is a dataset of 40,000 questions asked in conversational contexts paired with their gold context-independent (stand-alone) rewrite.

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