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        <title>End-to-End Sequential Metaphor Identification Inspired by Linguistic Theories</title>
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        <namePart type="given">Rui</namePart>
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            <namePart type="given">Anna</namePart>
            <namePart type="family">Korhonen</namePart>
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    <abstract>End-to-end training with Deep Neural Networks (DNN) is a currently popular method for metaphor identification. However, standard sequence tagging models do not explicitly take advantage of linguistic theories of metaphor identification. We experiment with two DNN models which are inspired by two human metaphor identification procedures. By testing on three public datasets, we find that our models achieve state-of-the-art performance in end-to-end metaphor identification.</abstract>
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    <identifier type="doi">10.18653/v1/P19-1378</identifier>
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%0 Conference Proceedings
%T End-to-End Sequential Metaphor Identification Inspired by Linguistic Theories
%A Mao, Rui
%A Lin, Chenghua
%A Guerin, Frank
%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 mao-etal-2019-end
%X End-to-end training with Deep Neural Networks (DNN) is a currently popular method for metaphor identification. However, standard sequence tagging models do not explicitly take advantage of linguistic theories of metaphor identification. We experiment with two DNN models which are inspired by two human metaphor identification procedures. By testing on three public datasets, we find that our models achieve state-of-the-art performance in end-to-end metaphor identification.
%R 10.18653/v1/P19-1378
%U https://aclanthology.org/P19-1378
%U https://doi.org/10.18653/v1/P19-1378
%P 3888-3898

Markdown (Informal)

[End-to-End Sequential Metaphor Identification Inspired by Linguistic Theories](https://aclanthology.org/P19-1378) (Mao et al., ACL 2019)

• End-to-End Sequential Metaphor Identification Inspired by Linguistic Theories (Mao et al., ACL 2019)

ACL

• Rui Mao, Chenghua Lin, and Frank Guerin. 2019. End-to-End Sequential Metaphor Identification Inspired by Linguistic Theories. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 3888–3898, Florence, Italy. Association for Computational Linguistics.