Improving Arabic dependency parsing with form-based and functional morphological features

Yuval Marton, Nizar Habash, Owen Rambow

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We explore the contribution of morphological features - both lexical and inflectional - to dependency parsing of Arabic, a morphologically rich language. Using controlled experiments, we find that definiteness, person, number, gender, and the undiacritzed lemma are most helpful for parsing on automatically tagged input. We further contrast the contribution of form-based and functional features, and show that functional gender and number (e.g., "broken plurals") and the related rationality feature improve over form-based features. It is the first time functional morphological features are used for Arabic NLP.

Original languageEnglish (US)
Title of host publicationACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics
Subtitle of host publicationHuman Language Technologies
Pages1586-1596
Number of pages11
StatePublished - 2011
Event49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-HLT 2011 - Portland, OR, United States
Duration: Jun 19 2011Jun 24 2011

Publication series

NameACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies
Volume1

Other

Other49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-HLT 2011
CountryUnited States
CityPortland, OR
Period6/19/116/24/11

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

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    Marton, Y., Habash, N., & Rambow, O. (2011). Improving Arabic dependency parsing with form-based and functional morphological features. In ACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (pp. 1586-1596). (ACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies; Vol. 1).