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        <title>Does it Make Sense? And Why? A Pilot Study for Sense Making and Explanation</title>
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    <name type="personal">
        <namePart type="given">Cunxiang</namePart>
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        <namePart type="given">Shuailong</namePart>
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    <name type="personal">
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    <abstract>Introducing common sense to natural language understanding systems has received increasing research attention. It remains a fundamental question on how to evaluate whether a system has the sense-making capability. Existing benchmarks measure common sense knowledge indirectly or without reasoning. In this paper, we release a benchmark to directly test whether a system can differentiate natural language statements that make sense from those that do not make sense. In addition, a system is asked to identify the most crucial reason why a statement does not make sense. We evaluate models trained over large-scale language modeling tasks as well as human performance, showing that there are different challenges for system sense-making.</abstract>
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%0 Conference Proceedings
%T Does it Make Sense? And Why? A Pilot Study for Sense Making and Explanation
%A Wang, Cunxiang
%A Liang, Shuailong
%A Zhang, Yue
%A Li, Xiaonan
%A Gao, Tian
%Y Korhonen, Anna
%Y Traum, David
%Y Màrquez, Lluís
%S Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
%D 2019
%8 July
%I Association for Computational Linguistics
%C Florence, Italy
%F wang-etal-2019-make
%X Introducing common sense to natural language understanding systems has received increasing research attention. It remains a fundamental question on how to evaluate whether a system has the sense-making capability. Existing benchmarks measure common sense knowledge indirectly or without reasoning. In this paper, we release a benchmark to directly test whether a system can differentiate natural language statements that make sense from those that do not make sense. In addition, a system is asked to identify the most crucial reason why a statement does not make sense. We evaluate models trained over large-scale language modeling tasks as well as human performance, showing that there are different challenges for system sense-making.
%R 10.18653/v1/P19-1393
%U https://aclanthology.org/P19-1393/
%U https://doi.org/10.18653/v1/P19-1393
%P 4020-4026

Markdown (Informal)

[Does it Make Sense? And Why? A Pilot Study for Sense Making and Explanation](https://aclanthology.org/P19-1393/) (Wang et al., ACL 2019)

• Does it Make Sense? And Why? A Pilot Study for Sense Making and Explanation (Wang et al., ACL 2019)

ACL

• Cunxiang Wang, Shuailong Liang, Yue Zhang, Xiaonan Li, and Tian Gao. 2019. Does it Make Sense? And Why? A Pilot Study for Sense Making and Explanation. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 4020–4026, Florence, Italy. Association for Computational Linguistics.