SOTAVerified

Metaphor Detection via Linguistics Enhanced Siamese Network

2022-10-01COLING 2022Code Available0· sign in to hype

Shenglong Zhang, Ying Liu

Code Available — Be the first to reproduce this paper.

Reproduce

Code

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.

Reproductions