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Ask what's missing and what's useful: Improving Clarification Question Generation using Global Knowledge

Bodhisattwa Prasad Majumder, Sudha Rao, Michel Galley, Julian McAuley
2021 Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies   unpublished

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The ability to generate clarification questions i.e., questions that identify useful missing information in a given context, is important in reducing ambiguity. Humans use previous experience with similar contexts to form a global view and compare it to the given context to ascertain what is missing and what is useful in the context. Inspired by this, we propose a model for clarification question generation where we first identify what is missing by taking a difference between the global and
more » ... local view and then train a model to identify what is useful and generate a question about it. Our model outperforms several baselines as judged by both automatic metrics and humans.
doi:10.18653/v1/2021.naacl-main.340 fatcat:lbsurm4obzgxbfssohjwnxmstu
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Bodhisattwa Prasad Majumder, Sudha Rao, Michel Galley, Julian McAuley. "Ask what's missing and what's useful: Improving Clarification Question Generation using Global Knowledge." Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021)