Character-Aware Neural Morphological Disambiguation

被引：8
|
作者：
Toleu, Alymzhan [1 ]
Tolegen, Gulmira [1 ]
Makazhanov, Aibek [1 ]
机构：
[1] Nazarbayev Univ, Natl Lab Astana, 53 Kabanbay Batyr Ave, Astana, Kazakhstan
来源：
PROCEEDINGS OF THE 55TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2017), VOL 2 | 2017年
关键词：
NETWORKS;
D O I：
10.18653/v1/P17-2105
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
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.
引用
收藏
页码：666 / 671
页数：6
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