Choosing features for classifying multiword expressions

Fuente: arXiv
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Main Author: Laporte, Eric
Format: Preprint
Published: 2026
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author Laporte, Eric
author_facet Laporte, Eric
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2605_11779
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Choosing features for classifying multiword expressions
Laporte, Eric
Computation and Language
I.7.0
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.
title Choosing features for classifying multiword expressions
topic Computation and Language
I.7.0
url https://arxiv.org/abs/2605.11779