Coreference resolution algorithm for Ukrainian-language texts using decision trees

S. D. Pogorilyy, P. V. Biletskyi


The paper examines the problem of coreference resolution in Ukrainian-language texts using decision trees. An application that uses vector representations of Elmo words and other characteristics for the automated formation of a decision tree has been developed. A set of prepared texts containing more than 360,000 words was used to form the decision tree and evaluate the accuracy of the algorithm. The decision tree created to determine whether a pair of objects is coreference was used to form clusters of coreference objects. Special metrics were used for comparison with the results obtained by other algorithms in the Ukrainian language.

Prombles in programming 2022; 3-4: 85-91


coreference resolution; natural language processing (NLP); decision trees; artificial intelligence (AI); vector words representation, neural networks


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