Metaphorical Polysemy Detection: Conventional Metaphor Meets Word Sense Disambiguation

Rowan Hall Maudslay, Simone Teufel


Abstract
Linguists distinguish between novel and conventional metaphor, a distinction which the metaphor detection task in NLP does not take into account. Instead, metaphoricity is formulated as a property of a token in a sentence, regardless of metaphor type. In this paper, we investigate the limitations of treating conventional metaphors in this way, and advocate for an alternative which we name ‘metaphorical polysemy detection’ (MPD). In MPD, only conventional metaphoricity is treated, and it is formulated as a property of word senses in a lexicon. We develop the first MPD model, which learns to identify conventional metaphors in the English WordNet. To train it, we present a novel training procedure that combines metaphor detection with ‘word sense disambiguation’ (WSD). For evaluation, we manually annotate metaphor in two subsets of WordNet. Our model significantly outperforms a strong baseline based on a state-of-the-art metaphor detection model, attaining an ROC-AUC score of .78 (compared to .65) on one of the sets. Additionally, when paired with a WSD model, our approach outperforms a state-of-the-art metaphor detection model at identifying conventional metaphors in text (.659 F1 compared to .626).
Anthology ID:
2022.coling-1.7
Volume:
Proceedings of the 29th International Conference on Computational Linguistics
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
65–77
Language:
URL:
https://aclanthology.org/2022.coling-1.7
DOI:
Bibkey:
Cite (ACL):
Rowan Hall Maudslay and Simone Teufel. 2022. Metaphorical Polysemy Detection: Conventional Metaphor Meets Word Sense Disambiguation. In Proceedings of the 29th International Conference on Computational Linguistics, pages 65–77, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):
Metaphorical Polysemy Detection: Conventional Metaphor Meets Word Sense Disambiguation (Maudslay & Teufel, COLING 2022)
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PDF:
https://aclanthology.org/2022.coling-1.7.pdf