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EMNLP2021Top-tier venue

Building and Evaluating Open-Domain Dialogue Corpora with Clarifying Questions

Mohammad Aliannejadi, Julia Kiseleva, Aleksandr Chuklin, Jeff Dalton, Mikhail Burtsev

2021Year
61Citations
24Top-tier citations

Abstract

Enabling open-domain dialogue systems to ask clarifying questions when appropriate is an important direction for improving the quality of the system response. Namely, for cases when a user request is not specific enough for a conversation system to provide an answer right away, it is desirable to ask a clarifying question to increase the chances of retrieving a satisfying answer. To address the problem of 'asking clarifying questions in opendomain dialogues': (1) we collect and release a new dataset focused on open-domain singleand multi-turn conversations, (2) we benchmark several state-of-the-art neural baselines, and (3) we propose a pipeline consisting of offline and online steps for evaluating the quality of clarifying questions in various dialogues. These contributions are suitable as a foundation for further research.

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