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This paper presents ContrastWSD, a RoBERTa-based metaphor detection modelthat integrates the Metaphor Identification Procedure (MIP) and Word SenseDisambiguation (WSD) to extract and contrast the contextual meaning with thebasic meaning of a word to determine whether it is used metaphorically in asentence. By utilizing the word senses derived from a WSD model, our modelenhances the metaphor detection process and outperforms other methods that relysolely on contextual embeddings or integrate only the basic definitions andother external knowledge. We evaluate our approach on various benchmarkdatasets and compare it with strong baselines, indicating the effectiveness inadvancing metaphor detection.

ContrastWSD: Enhancing Metaphor Detection with Word Sense Disambiguation Following the Metaphor Identification Procedure