A free/open-source hybrid morphological disambiguation tool for Kazakh

Zhenisbek Assylbekov, Jonathan Washington, Francis Tyers, Assulan Nurkas, Aida Sundetova, Aidana Karibayeva, Balzhan Abduali, Dina Amirova

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper presents the results of developing a morphological disambiguation tool for Kazakh. Starting with a previously developed rule-based approach, we tried to cope with the complex morphology of Kazakh by breaking up lexical forms across their derivational boundaries into inflectional groups and modeling their behavior with statistical methods. A hybrid rule-based/statistical approach appears to benefit morphological disambiguation demonstrating a per-token accuracy of 91% in running text.
Original languageEnglish
Publication statusPublished - 2016
EventThe First International Conference on Turkic Computational Linguistics - Konya, Turkey
Duration: Apr 2 2016Apr 8 2016
http://nur.nu.edu.kz/bitstream/handle/123456789/1692/kaz-tagger.pdf?sequence=1

Conference

ConferenceThe First International Conference on Turkic Computational Linguistics
Abbreviated titleTurCLing 2016
CountryTurkey
CityKonya
Period4/2/164/8/16
Internet address

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