Abstract
We propose a unified framework that enables us to consider various aspects of contextualization at different levels to better identify the idiomaticity of multi-word expressions. Through extensive experiments, we demonstrate that our approach based on the inter- and inner-sentence context of a target MWE is effective in improving the performance of related models. We also share our experience in detail on the task of SemEval-2022 Task 2 such that future work on the same task can be benefited from this.
Cite
CITATION STYLE
Joung, Y., & Kim, T. (2022). HYU at SemEval-2022 Task 2: Effective Idiomaticity Detection with Consideration at Different Levels of Contextualization. In SemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop (pp. 151–157). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.semeval-1.17
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