Bridging the Gap: Attending to Discontinuity in Identification of Multiword Expressions (N19-1)
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| Challenge: | Existing approaches to identify discontinuous multiword expressions are limited in dealing with discontinuous occurrences. |
| Approach: | They propose a method to tag Multiword Expressions using a language-independent deep learning architecture to target discontinuity. |
| Outcome: | The proposed model outperforms baseline models on a multilingual dataset and scores higher than baseline models. |
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Yusuke Ide, Joshua Tanner, Adam Nohejl, Jacob Hoffman, Justin Vasselli, Hidetaka Kamigaito, Taro Watanabe
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| Challenge: | Headless multi-word expressions are frequent in natural language but lack internal syntactic dominance relations. |
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| Challenge: | Multi-Word Expressions (MWEs) are common in every language, but they are not translated by cross-lingual word embeddings. |
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Cross-type French Multiword Expression Identification with Pre-trained Masked Language Models (2024.lrec-main)
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| Challenge: | Multiword expressions (MWEs) have linguistic features that distinguish them from regular word groupings. |
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