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The paper contains the description of a semi-authomatic method for the detection of typologically relevant semantic shifts in the world’s languages. The algorithm extracts colexified pairs of meanings from polysemous words in digitised bilingual dictionaries. A machine learning classifier helps to separate those semantic shifts that are relevant to the lexical typology. Clustering is applied to group similar pairs of meanings into semantic shifts.
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Gruntov et al. (2023) studied this question.
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