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This research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP19577922).
This paper describes a method and technology for processing natural language texts and
extracting data from the text that correspond to the semantics of an ontological model. The proposed
method is distinguished by the use of a Large Language Model algorithm for text analysis. The
extracted data are stored in an intermediate format, after which individuals and properties that reflect
the specified semantics are programmatically created in the ontology. The proposed technology
is implemented using the example of an ontological model that describes the geographical configuration
and administrative–territorial division of Kazakhstan. The proposed method and technology
can be applied in any subject areas for which ontological models have been developed. The results
of the study can significantly improve the efficiency of using knowledge bases based on semantic
networks by converting texts in natural languages into semantically linked data.
