Papers with MWE identification
MWE as WSD: Solving Multiword Expression Identification with Word Sense Disambiguation (2023.findings-emnlp)
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| Challenge: | Recent approaches to word sense disambiguation use encodings of the sense gloss and context information to improve performance. |
| Approach: | They propose a poly-encoder architecture which uses the sense gloss to improve WSD performance. |
| Outcome: | The proposed approach outperforms the state-of-the-art in word sense disambiguation by 1.9 F1 points and on the PARSEME 1.1 English dataset. |
Identification of Multiword Expressions in Tweets for Hate Speech Detection (2022.lrec-1)
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| Challenge: | Multiword expression (MWE) identification in tweets is a complex task due to the complex linguistic nature of MWEs combined with the non-standard language use in social networks. |
| Approach: | They propose a new architecture for incorporating multiword expression features into tweets to improve their accuracy. |
| Outcome: | The proposed system outperforms existing systems on the hate speech detection task on English Twitter. |
Detecting Multiword Expression Type Helps Lexical Complexity Assessment (2020.lrec-1)
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| Challenge: | Multiword expressions (MWEs) represent lexemes that should be treated as single lexical units due to their idiosyncratic nature. |
| Approach: | They re-annotate a complex word identification shared task 2018 dataset . they find that a lexical complexity assessment system benefits from the information . |
| Outcome: | The proposed dataset provides valuable information for the text simplification community. |
CoAM: Corpus of All-Type Multiword Expressions (2025.acl-long)
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Yusuke Ide, Joshua Tanner, Adam Nohejl, Jacob Hoffman, Justin Vasselli, Hidetaka Kamigaito, Taro Watanabe
| Challenge: | Existing datasets for multiword expressions are inconsistently annotated, limited to a single type of MWE, or limited in size. |
| Approach: | They propose to use a new interface to generate MWE annotations for the first time in a dataset of MWE identification. |
| Outcome: | The proposed model outperforms existing models on the DiMSUM dataset. |