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        <title>Is It Dish Washer Safe? Automatically Answering “Yes/No” Questions Using Customer Reviews</title>
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    <name type="personal">
        <namePart type="given">Daria</namePart>
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            <title>Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop</title>
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            <namePart type="given">Sudipta</namePart>
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        <name type="personal">
            <namePart type="given">Farah</namePart>
            <namePart type="family">Nadeem</namePart>
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            <namePart type="given">Laura</namePart>
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            <namePart type="given">Greg</namePart>
            <namePart type="family">Durrett</namePart>
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            <namePart type="given">Na-Rae</namePart>
            <namePart type="family">Han</namePart>
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            <publisher>Association for Computational Linguistics</publisher>
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    <abstract>It has become commonplace for people to share their opinions about all kinds of products by posting reviews online. It has also become commonplace for potential customers to do research about the quality and limitations of these products by posting questions online. We test the extent to which reviews are useful in question-answering by combining two Amazon datasets and focusing our attention on yes/no questions. A manual analysis of 400 cases reveals that the reviews directly contain the answer to the question just over a third of the time. Preliminary reading comprehension experiments with this dataset prove inconclusive, with accuracy in the range 50-66%.</abstract>
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%0 Conference Proceedings
%T Is It Dish Washer Safe? Automatically Answering “Yes/No” Questions Using Customer Reviews
%A Dzendzik, Daria
%A Vogel, Carl
%A Foster, Jennifer
%Y Kar, Sudipta
%Y Nadeem, Farah
%Y Burdick, Laura
%Y Durrett, Greg
%Y Han, Na-Rae
%S Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota
%F dzendzik-etal-2019-dish
%X It has become commonplace for people to share their opinions about all kinds of products by posting reviews online. It has also become commonplace for potential customers to do research about the quality and limitations of these products by posting questions online. We test the extent to which reviews are useful in question-answering by combining two Amazon datasets and focusing our attention on yes/no questions. A manual analysis of 400 cases reveals that the reviews directly contain the answer to the question just over a third of the time. Preliminary reading comprehension experiments with this dataset prove inconclusive, with accuracy in the range 50-66%.
%R 10.18653/v1/N19-3001
%U https://aclanthology.org/N19-3001
%U https://doi.org/10.18653/v1/N19-3001
%P 1-6

Markdown (Informal)

[Is It Dish Washer Safe? Automatically Answering “Yes/No” Questions Using Customer Reviews](https://aclanthology.org/N19-3001) (Dzendzik et al., NAACL 2019)

• Is It Dish Washer Safe? Automatically Answering “Yes/No” Questions Using Customer Reviews (Dzendzik et al., NAACL 2019)

ACL

• Daria Dzendzik, Carl Vogel, and Jennifer Foster. 2019. Is It Dish Washer Safe? Automatically Answering “Yes/No” Questions Using Customer Reviews. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop, pages 1–6, Minneapolis, Minnesota. Association for Computational Linguistics.