HIT at SemEval-2022 Task 2: Pre-trained Language Model for Idioms Detection

• URL: http://arxiv.org/abs/2204.06145v1
• Date: Wed, 13 Apr 2022 02:45:04 GMT
• Title: HIT at SemEval-2022 Task 2: Pre-trained Language Model for Idioms Detection
• Authors: Zheng Chu, Ziqing Yang, Yiming Cui, Zhigang Chen, Ming Liu
• Abstract summary: The same multi-word expressions may have different meanings in different sentences. They can be divided into two categories, which are literal meaning and idiomatic meaning. We use a pre-trained language model, which can provide a context-aware sentence embedding.
• Score: 23.576133853110324
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The same multi-word expressions may have different meanings in different sentences. They can be mainly divided into two categories, which are literal meaning and idiomatic meaning. Non-contextual-based methods perform poorly on this problem, and we need contextual embedding to understand the idiomatic meaning of multi-word expressions correctly. We use a pre-trained language model, which can provide a context-aware sentence embedding, to detect whether multi-word expression in the sentence is idiomatic usage.

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