SEMANTIC ANALYSIS OF UZBEK LANGUAGE TEXTS USING THE INCEPTION PLATFORM

This article examines the application of the INCEpTION platform to the semantic analysis of Uzbek-language texts, emphasizing linguistic annotation, knowledge representation, and the development of computational language resources. INCEpTION is a web-based semantic annotation platform that supports collaborative annotation, knowledge-assisted labeling, and machine-learning-assisted annotation workflows. The study investigates how its functionalities can be adapted to the linguistic characteristics of Uzbek, an agglutinative Turkic language with extensive morphological variation and relatively flexible word order. Particular attention is given to named entity recognition, semantic relation annotation, word sense disambiguation, and the identification of context-dependent meanings. The research adopts a descriptive and comparative methodological approach based on established studies in natural language processing, semantic annotation, and computational linguistics. The article proposes an annotation framework for Uzbek texts and identifies methodological challenges associated with morphological complexity, contextual ambiguity, annotation consistency, and limited annotated resources. The findings indicate that INCEpTION provides a technically suitable environment for organizing human-supervised semantic annotation projects, although its effectiveness for Uzbek depends on the availability of appropriate linguistic guidelines, annotated datasets, and compatible language-processing models. The study contributes to the methodological foundations of Uzbek natural language processing and outlines practical directions for developing semantically annotated Uzbek corpora.