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        <title>Verbal Multiword Expressions for Identification of Metaphor</title>
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            <title>Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics</title>
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            <namePart type="given">Dan</namePart>
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    <abstract>Metaphor is a linguistic device in which a concept is expressed by mentioning another. Identifying metaphorical expressions, therefore, requires a non-compositional understanding of semantics. Multiword Expressions (MWEs), on the other hand, are linguistic phenomena with varying degrees of semantic opacity and their identification poses a challenge to computational models. This work is the first attempt at analysing the interplay of metaphor and MWEs processing through the design of a neural architecture whereby classification of metaphors is enhanced by informing the model of the presence of MWEs. To the best of our knowledge, this is the first “MWE-aware” metaphor identification system paving the way for further experiments on the complex interactions of these phenomena. The results and analyses show that this proposed architecture reach state-of-the-art on two different established metaphor datasets.</abstract>
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%0 Conference Proceedings
%T Verbal Multiword Expressions for Identification of Metaphor
%A Rohanian, Omid
%A Rei, Marek
%A Taslimipoor, Shiva
%A Ha, Le An
%Y Jurafsky, Dan
%Y Chai, Joyce
%Y Schluter, Natalie
%Y Tetreault, Joel
%S Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F rohanian-etal-2020-verbal
%X Metaphor is a linguistic device in which a concept is expressed by mentioning another. Identifying metaphorical expressions, therefore, requires a non-compositional understanding of semantics. Multiword Expressions (MWEs), on the other hand, are linguistic phenomena with varying degrees of semantic opacity and their identification poses a challenge to computational models. This work is the first attempt at analysing the interplay of metaphor and MWEs processing through the design of a neural architecture whereby classification of metaphors is enhanced by informing the model of the presence of MWEs. To the best of our knowledge, this is the first “MWE-aware” metaphor identification system paving the way for further experiments on the complex interactions of these phenomena. The results and analyses show that this proposed architecture reach state-of-the-art on two different established metaphor datasets.
%R 10.18653/v1/2020.acl-main.259
%U https://aclanthology.org/2020.acl-main.259
%U https://doi.org/10.18653/v1/2020.acl-main.259
%P 2890-2895

Markdown (Informal)

[Verbal Multiword Expressions for Identification of Metaphor](https://aclanthology.org/2020.acl-main.259) (Rohanian et al., ACL 2020)

• Verbal Multiword Expressions for Identification of Metaphor (Rohanian et al., ACL 2020)

ACL

• Omid Rohanian, Marek Rei, Shiva Taslimipoor, and Le An Ha. 2020. Verbal Multiword Expressions for Identification of Metaphor. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 2890–2895, Online. Association for Computational Linguistics.