LLM-Powered Natural Language Text Processing for Ontology Enrichment
Mukanova A. Milosz M. Dauletkaliyeva A. Nazyrova A. Yelibayeva G. Kuzin D. Kussepova L.
July 2024Multidisciplinary Digital Publishing Institute (MDPI)
Applied Sciences (Switzerland)
2024#14Issue 13
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.
ChatGPT , geographic question answering system , Large Language Model , natural language processing , ontology , Semantic Web
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Higher School of Information Technology and Engineering, Astana International University, 8 Kabanbay Batyr Av., Astana, 010000, Kazakhstan
Department of Computer Science, Lublin University of Technology, 36B Nadbystrzycka Str., Lublin, 20-618, Poland
Faculty of Information Technologies, L.N. Gumilyov Eurasian National University, 2 Satpayev Str, Astana, 010008, Kazakhstan
Higher School of Information Technology and Engineering
Department of Computer Science
Faculty of Information Technologies
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