Slowinska, Ewa2024-06-172024-06-172024-06-17https://hdl.handle.net/2077/81767The scope of this thesis is on Lexical Semantic Change (LSC) and its automatic detection in the Polish language. Following Cassotti et al. (2023)’s findings, the following thesis leverages XL-Lexeme, a transformerbased bi-encoder model, to perform LSC detection on the Polish Parliamentary Corpus divided into two time periods: (1) 1919-1961 and (2) 1989-2023. The aim of this thesis is to examine the performance of XL-Lexeme with a Polish dataset and to state what kind of changes occurred between the two predefined time periods. The results suggest a rather robust performance of XL-Lexeme, coinciding with the judgements of a native speaker of Polish, however the influence of context and occasional annotation errors hinder the reliability of the results. The types of changes detected through close-reading include semantic widening and narrowing as well as changes in the meaning distribution, which are often be related to technological and political advancements. Additional WiC task performed on a small portion of annotated sentence pairs further confirms XL-Lexeme’s swift handling of Polish language, yielding a precision as high as 0.971 but falling behind on recall which amounts to 0.684.engLanguage TechnologyText