Metaphor Detection via Linguistics Enhanced Siamese Network

Shenglong Zhang; Ying Liu

Metaphor Detection via Linguistics Enhanced Siamese Network

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Abstract

In this paper we present MisNet, a novel model for word level metaphor detection. MisNet converts two linguistic rules, i.e., Metaphor Identification Procedure (MIP) and Selectional Preference Violation (SPV) into semantic matching tasks. MIP module computes the similarity between the contextual meaning and the basic meaning of a target word. SPV module perceives the incongruity between target words and their contexts. To better represent basic meanings, MisNet utilizes dictionary resources. Empirical results indicate that MisNet achieves competitive performance on several datasets.

Anthology ID:: 2022.coling-1.364
Volume:: Proceedings of the 29th International Conference on Computational Linguistics
Month:: October
Year:: 2022
Address:: Gyeongju, Republic of Korea
Editors:: Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
Venue:: COLING
SIG:
Publisher:: International Committee on Computational Linguistics
Note:
Pages:: 4149–4159
Language:
URL:: https://aclanthology.org/2022.coling-1.364/
DOI:
Bibkey:
Cite (ACL):: Shenglong Zhang and Ying Liu. 2022. Metaphor Detection via Linguistics Enhanced Siamese Network. In Proceedings of the 29th International Conference on Computational Linguistics, pages 4149–4159, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):: Metaphor Detection via Linguistics Enhanced Siamese Network (Zhang & Liu, COLING 2022)
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PDF:: https://aclanthology.org/2022.coling-1.364.pdf

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@inproceedings{zhang-liu-2022-metaphor,
    title = "Metaphor Detection via Linguistics Enhanced {S}iamese Network",
    author = "Zhang, Shenglong  and
      Liu, Ying",
    editor = "Calzolari, Nicoletta  and
      Huang, Chu-Ren  and
      Kim, Hansaem  and
      Pustejovsky, James  and
      Wanner, Leo  and
      Choi, Key-Sun  and
      Ryu, Pum-Mo  and
      Chen, Hsin-Hsi  and
      Donatelli, Lucia  and
      Ji, Heng  and
      Kurohashi, Sadao  and
      Paggio, Patrizia  and
      Xue, Nianwen  and
      Kim, Seokhwan  and
      Hahm, Younggyun  and
      He, Zhong  and
      Lee, Tony Kyungil  and
      Santus, Enrico  and
      Bond, Francis  and
      Na, Seung-Hoon",
    booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea",
    publisher = "International Committee on Computational Linguistics",
    url = "https://aclanthology.org/2022.coling-1.364/",
    pages = "4149--4159",
    abstract = "In this paper we present MisNet, a novel model for word level metaphor detection. MisNet converts two linguistic rules, i.e., Metaphor Identification Procedure (MIP) and Selectional Preference Violation (SPV) into semantic matching tasks. MIP module computes the similarity between the contextual meaning and the basic meaning of a target word. SPV module perceives the incongruity between target words and their contexts. To better represent basic meanings, MisNet utilizes dictionary resources. Empirical results indicate that MisNet achieves competitive performance on several datasets."
}

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%0 Conference Proceedings
%T Metaphor Detection via Linguistics Enhanced Siamese Network
%A Zhang, Shenglong
%A Liu, Ying
%Y Calzolari, Nicoletta
%Y Huang, Chu-Ren
%Y Kim, Hansaem
%Y Pustejovsky, James
%Y Wanner, Leo
%Y Choi, Key-Sun
%Y Ryu, Pum-Mo
%Y Chen, Hsin-Hsi
%Y Donatelli, Lucia
%Y Ji, Heng
%Y Kurohashi, Sadao
%Y Paggio, Patrizia
%Y Xue, Nianwen
%Y Kim, Seokhwan
%Y Hahm, Younggyun
%Y He, Zhong
%Y Lee, Tony Kyungil
%Y Santus, Enrico
%Y Bond, Francis
%Y Na, Seung-Hoon
%S Proceedings of the 29th International Conference on Computational Linguistics
%D 2022
%8 October
%I International Committee on Computational Linguistics
%C Gyeongju, Republic of Korea
%F zhang-liu-2022-metaphor
%X In this paper we present MisNet, a novel model for word level metaphor detection. MisNet converts two linguistic rules, i.e., Metaphor Identification Procedure (MIP) and Selectional Preference Violation (SPV) into semantic matching tasks. MIP module computes the similarity between the contextual meaning and the basic meaning of a target word. SPV module perceives the incongruity between target words and their contexts. To better represent basic meanings, MisNet utilizes dictionary resources. Empirical results indicate that MisNet achieves competitive performance on several datasets.
%U https://aclanthology.org/2022.coling-1.364/
%P 4149-4159

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Markdown (Informal)

[Metaphor Detection via Linguistics Enhanced Siamese Network](https://aclanthology.org/2022.coling-1.364/) (Zhang & Liu, COLING 2022)

Metaphor Detection via Linguistics Enhanced Siamese Network (Zhang & Liu, COLING 2022)

ACL

Shenglong Zhang and Ying Liu. 2022. Metaphor Detection via Linguistics Enhanced Siamese Network. In Proceedings of the 29th International Conference on Computational Linguistics, pages 4149–4159, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.