Statistical Morphological Disambiguation for Kazakh Language

Abstract

This paper presents the results of developing a statistical model for morphological disambiguation of Kazakh text. Starting with basic assumptions we tried to cope with the complex morphology of Kazakh language by breaking up lexical forms across their derivational boundaries into inflectional groups and modeling their behavior with statistical methods. We also provide maximum likelihood estimates for the parameters and an effective way to perform disambiguation with the Viterbi algorithm.