HIT at SemEval-2022 Task 2: Pre-trained Language Model for Idioms Detection
Computation and Language
2022-04-14 v1
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.
Cite
@article{arxiv.2204.06145,
title = {HIT at SemEval-2022 Task 2: Pre-trained Language Model for Idioms Detection},
author = {Zheng Chu and Ziqing Yang and Yiming Cui and Zhigang Chen and Ming Liu},
journal= {arXiv preprint arXiv:2204.06145},
year = {2022}
}
Comments
6 pages; SemEval-2022 Task 2