Choosing features for classifying multiword expressions
Computation and Language
2026-05-13 v1
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.
Keywords
Cite
@article{arxiv.2605.11779,
title = {Choosing features for classifying multiword expressions},
author = {Eric Laporte},
journal= {arXiv preprint arXiv:2605.11779},
year = {2026}
}