Towards a Data-driven Morphological Analysis of Kazakh Language
Olzhas Makhambetov, Aibek Makazhanov, Zhandos Yessenbayev, Islam Sabyrgaliyev, Anuar Sharafudinov · DergiPark (Istanbul University) · 2014
We propose a method for complete morphological analysis of Kazakh language that accounts for both inflectional and derivational morphology. Our method is data-driven and does not require manually generated rules, which makes it convenient for analyzing agglutinative languages. The intuition behind our approach is to label morphemes with so called transition labels, i.e. labels that encode grammatical functions of morphemes as transitions between corresponding POS, and use transitivity to ease the analysis. We evaluate our method on a fair-sized sample of real data and report encouraging results.