Character-Aware Neural Morphological Disambiguation

Alymzhan Toleu; Gulmira Tolegen; Aibek Makazhanov

Character-Aware Neural Morphological Disambiguation

Alymzhan Toleu, Gulmira Tolegen, Aibek Makazhanov

Laboratory of computational materials science for energy application

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Citations (Scopus)

Abstract

We develop a language-independent, deep learning-based approach to the task of morphological disambiguation. Guided by the intuition that the correct analysis should be ``most similar'' to the context, we propose dense representations for morphological analyses and surface context and a simple yet effective way of combining the two to perform disambiguation. Our approach improves on the language-dependent state of the art for two agglutinative languages (Turkish and Kazakh) and can be potentially applied to other morphologically complex languages.

Original language	Undefined/Unknown
Title of host publication	Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Place of Publication	Vancouver, Canada
Publisher	Association for Computational Linguistics (ACL)
Pages	666-671
Number of pages	6
Publication status	Published - Jul 1 2017

Access to Document

http://aclweb.org/anthology/P17-2105

Cite this

Character-Aware Neural Morphological Disambiguation. / Toleu, Alymzhan; Tolegen, Gulmira; Makazhanov, Aibek.

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Vancouver, Canada : Association for Computational Linguistics (ACL), 2017. p. 666-671.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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BT - Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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