EXPLORING LEXICAL SEMANTIC CHANGE IN POLISH USING XL-LEXEME

Abstract

The 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.