Verbal Multiword Expressions for Identification of Metaphor

Omid Rohanian, Marek Rei, Shiva Taslimipoor, Le An Ha


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.
Anthology ID:
2020.acl-main.259
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2020
Address:
Online
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2890–2895
Language:
URL:
https://www.aclweb.org/anthology/2020.acl-main.259
DOI:
10.18653/v1/2020.acl-main.259
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.acl-main.259.pdf
Video:
 http://slideslive.com/38929343