Semantically motivated Hebrew verb-noun multi-word expressions identification

Chaya Liebeskind, Yaakov HaCohen-Kerner

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Identification of Multi-Word Expressions (MWEs) lies at the heart of many natural language processing applications. In this research, we deal with a particular type of Hebrew MWEs, Verb-Noun MWEs (VN-MWEs), which combine a verb and a noun with or without other words. Most prior work on MWEs classification focused on linguistic and statistical information. In this paper, we claim that it is essential to utilize semantic information. To this end, we propose a semantically motivated indicator for classifying VN-MWE and define features that are related to various semantic spaces and combine them as features in a supervised classification framework. We empirically demonstrate that our semantic feature set yields better performance than the common linguistic and statistical feature sets and that combining semantic features contributes to the VN-MWEs identification task.

Original languageEnglish
Title of host publicationCOLING 2016 - 26th International Conference on Computational Linguistics, Proceedings of COLING 2016
Subtitle of host publicationTechnical Papers
PublisherAssociation for Computational Linguistics, ACL Anthology
Pages1242-1253
Number of pages12
ISBN (Print)9784879747020
StatePublished - 2016
Externally publishedYes
Event26th International Conference on Computational Linguistics, COLING 2016 - Osaka, Japan
Duration: 11 Dec 201616 Dec 2016

Publication series

NameCOLING 2016 - 26th International Conference on Computational Linguistics, Proceedings of COLING 2016: Technical Papers

Conference

Conference26th International Conference on Computational Linguistics, COLING 2016
Country/TerritoryJapan
CityOsaka
Period11/12/1616/12/16

Bibliographical note

Publisher Copyright:
© 1963-2018 ACL.

Funding

We would like to express our deep gratitude to Avital Day, our research assistant, for her help in programming and carrying out the research experiments. We would also like to acknowledge the networking support by the COST Action IC1207: PARSEME: PARSing and Multi-word Expressions. This work was partially funded by an internal research grant from Jerusalem College of Technology, Lev Academic Center.

FundersFunder number
Jerusalem College of Technology
Jerusalem College of Technology - Lev Academic Center

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