Abstract
We present a method for extracting Multiword Expressions (MWEs) based on the immediate context they occur in, using a supervised model. We show some of these contextual features can be very discriminant and combining them with MWE-specific features results in a relatively accurate extraction. We define context as a sequential structure and not a bag of words, consequently, it becomes much more informative about MWEs.
Cite
CITATION STYLE
Farahmand, M., & Martins, R. (2014). A supervised model for extraction of multiword expressions based on statistical context features. In MWE 2014 - Proceedings of the 10th Workshop on Multiword Expressions, in conjunction with the 14th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2014 (pp. 10–16). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/w14-0802
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