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Choosing features for classifying multiword expressions

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Computer Science > Computation and Language

arXiv:2605.11779 (cs)
[Submitted on 12 May 2026]

Title:Choosing features for classifying multiword expressions

Authors:Eric Laporte
View a PDF of the paper titled Choosing features for classifying multiword expressions, by Eric Laporte
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Abstract:Multiword expressions (MWEs) are a heterogeneous set with a glaring need for classifications. Designing a satisfactory classification involves choosing features. In the case of MWEs, many features are a priori available. Not all features are equal in terms of how reliably MWEs can be assigned to classes. Accordingly, resulting classifications may be more or less fruitful for computational use. I outline an enhanced classification. In order to increase its suitability for many languages, I use previous works taking into account various languages.
Subjects: Computation and Language (cs.CL)
ACM classes: I.7.0
Cite as: arXiv:2605.11779 [cs.CL]
  (or arXiv:2605.11779v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2605.11779
arXiv-issued DOI via DataCite (pending registration)
Journal reference: Multiword expressions: Insights from a multi-lingual perspective, 2018, Language Science Press, pp.143-186
Related DOI: https://doi.org/10.5281/zenodo.1182597
DOI(s) linking to related resources

Submission history

From: Eric Laporte [view email]
[v1] Tue, 12 May 2026 08:48:31 UTC (695 KB)
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