STRUCTURING OF MOTION AND STATE-EXPRESSING VERBS IN UZBEK LANGUAGE SYNSETS

This thesis explores the structuring of motion and state-expressing verbs in Uzbek language synsets, emphasizing the importance of semantic accuracy and computational methodologies in linguistic research. It discusses the principles of verb synset formation, including synonym selection, contextual verification, and differentiation of polysemous verbs. The role of lexical databases such as WordNet and NLP-based techniques in automating synset development is examined. The findings highlight the need for a balance between computational efficiency and linguistic expertise to ensure precise semantic grouping, ultimately enhancing natural language processing applications and linguistic research.