UZBEK TAGSET: CREATING A LIST OF MORPHOLOGICAL AND SYNTACTIC TAGS FOR BUILDING MACHINE LEARNING MODELS FOR THE UZBEK LANGUAGE

The aim of this study is to develop a comprehensive list of syntactic and morphological tags in Uzbek, which aims to create a dataset for natural language processing (NLP) problems in Uzbek. The study involves a systematic analysis of Uzbek grammar, morphology, and syntax, and aims to identify and classify relevant linguistic features. Based on existing tagset models for other languages and taking into account the specific features of the Uzbek language, we propose a hierarchical tagset structure that includes word classes, morphological features, and syntactic functions. A Hidden Markov Model (HMM) was built to solve the POS tagging NLP task using the created tagset.