Using Conceptual Norms for Metaphor Detection

Mingyu Wan, Kathleen Ahrens, Rong Xiang, Emmanuele Chersoni, Menghan Jiang, Qi Su, Chu-ren Huang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

This paper reports a linguistically-enriched method of detecting token-level metaphors for the second shared task on Metaphor Detection. We participate in all four phases of competition with both datasets, i.e. Verbs and AllPOS on the VUA and the TOFEL datasets. We use the modality exclusivity and embodiment norms for constructing a conceptual representation of the nodes and the context. Our system obtains an F-score of 0.652 for the VUA Verbs track, which is 5% higher than the strong baselines. The experimental results across models and datasets indicate the salient contribution of using modality exclusivity and modality shift information for predicting metaphoricity.
Original languageEnglish
Title of host publicationProceedings of The Second Workshop on Figurative Language Processing
PublisherAssociation for Computational Linguistics (ACL)
Pages104-109
Publication statusPublished - Jul 2020

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