In the thesis, we developed a procedure for discovering new word meanings. We extracted the list of observed words from the word-sense disambiguation dataset. Sentences containing the observed word were obtained from the news database from the Event Registry service. We represented the words with vectors using the models multilingual-BERT-Base, Cased and SloBERTa and clustered them in various ways. We compared the results with the data from the disambiguation dataset and manually checked some words with known semantic shifts. The obtained results are not promising. We believe that the main reason is an unsuitable text database.
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