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        <title>Detecting Asymmetric Semantic Relations in Context: A Case-Study on Hypernymy Detection</title>
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        <namePart type="given">Yogarshi</namePart>
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            <namePart type="family">Ide</namePart>
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        <name type="personal">
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    <abstract>We introduce WHiC, a challenging testbed for detecting hypernymy, an asymmetric relation between words. While previous work has focused on detecting hypernymy between word types, we ground the meaning of words in specific contexts drawn from WordNet examples, and require predictions to be sensitive to changes in contexts. WHiC lets us analyze complementary properties of two approaches of inducing vector representations of word meaning in context. We show that such contextualized word representations also improve detection of a wider range of semantic relations in context.</abstract>
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    <identifier type="doi">10.18653/v1/S17-1004</identifier>
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%0 Conference Proceedings
%T Detecting Asymmetric Semantic Relations in Context: A Case-Study on Hypernymy Detection
%A Vyas, Yogarshi
%A Carpuat, Marine
%Y Ide, Nancy
%Y Herbelot, Aurélie
%Y Màrquez, Lluís
%S Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada
%F vyas-carpuat-2017-detecting
%X We introduce WHiC, a challenging testbed for detecting hypernymy, an asymmetric relation between words. While previous work has focused on detecting hypernymy between word types, we ground the meaning of words in specific contexts drawn from WordNet examples, and require predictions to be sensitive to changes in contexts. WHiC lets us analyze complementary properties of two approaches of inducing vector representations of word meaning in context. We show that such contextualized word representations also improve detection of a wider range of semantic relations in context.
%R 10.18653/v1/S17-1004
%U https://aclanthology.org/S17-1004
%U https://doi.org/10.18653/v1/S17-1004
%P 33-43

Markdown (Informal)

[Detecting Asymmetric Semantic Relations in Context: A Case-Study on Hypernymy Detection](https://aclanthology.org/S17-1004) (Vyas & Carpuat, *SEM 2017)

• Detecting Asymmetric Semantic Relations in Context: A Case-Study on Hypernymy Detection (Vyas & Carpuat, *SEM 2017)

ACL

• Yogarshi Vyas and Marine Carpuat. 2017. Detecting Asymmetric Semantic Relations in Context: A Case-Study on Hypernymy Detection. In Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017), pages 33–43, Vancouver, Canada. Association for Computational Linguistics.