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Methods of Morphological and Syntactic Analysis for the Uzbek Language

Elov Botir BoltayevichTashkent State University of Uzbek Language and Literature named Alisher Navo’i,Dept. of Computational Linguistics and Digital Technologies,Tashkent,UzbekistanAbdullayeva Oqila Xolmo ‘minovnaTashkent State University of Uzbek Language and Literature named Alisher Navo’i,Dept. of Computational Linguistics and Digital Technologies,Tashkent,UzbekistanAbdullayeva Firuza SharipovnaBukhara State University,Dept. of Social and Political Sciences,Bukhara,UzbekistanAlavutdinova Nadira GaniyevnaNational University of Uzbekistan named after Mirzo Ulugbek,Tashkent,Uzbekistan
2025
ABI

Аннотация

The linguistic features of the Uzbek language - complex agglutinative morphology, free word order, and limited resources - necessitate a specialized approach and thorough research in the application of morphological and syntactic methods. Within the framework of the study, morphological analysis methods and syntactic analysis methods are reviewed based on scientific sources. Each section presents the existing advantages and disadvantages, experience of their use in the Uzbek language, as well as a comparative analysis with foreign languages. Rule-based methods, statistical models (HMM, CRF, etc.), Neural network-based approaches (BiLSTM-CRF, seq2seq) of morphological analysis in the Uzbek language are discussed, and the results are given in examples and percentages. It is shown that syntactic parsing is implemented using dependency and constituency parsing analysis methods. The issue of building a UD treebank for the Uzbek language with SOV order is considered. The impact of complex morphological structure and free word order in sentences on the construction of parsers is highlighted. As a result of the studied approaches, the issue of building hybrid parsers, integrating them with morphological analysis and assigning grammatical categories of words to the parser is raised. Also, the development of neural constituency parsers based on neural networks and the effectiveness of the results obtained from them are analyzed.

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