HYU at SemEval-2022 Task 2: Effective Idiomaticity Detection with Consideration at Different Levels of Contextualization

• URL: http://arxiv.org/abs/2206.11854v1
• Date: Wed, 1 Jun 2022 10:45:40 GMT
• Title: HYU at SemEval-2022 Task 2: Effective Idiomaticity Detection with Consideration at Different Levels of Contextualization
• Authors: Youngju Joung, Taeuk Kim
• Abstract summary: We propose a unified framework that enables us to consider various aspects of contextualization at different levels. We show that our approach is effective in improving the performance of related models.
• Score: 6.850627526999892
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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 Tasks 2 such that future work on the same task can be benefited from this.

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