Proceedings of the Annual Meeting of the Cognitive Science Society

The diversity of a word’s contexts affects its acquisition andprocessing. Can differences between word types such asmonosemes (unambiguous words), polysemes (multiple relatedsenses), and homonyms (multiple unrelated meanings) be re-lated to distributional properties of these words? We tested fortraces of number and relatedness of meaning in vector repre-sentations by comparing the distance between words of eachtype and vector representations of various “contexts”: their dic-tionary definitions (an extreme disambiguating context), theiruse in film subtitles (a natural context), and their semanticneighbours in vector space (a vector-space-internal context).Whereas dictionary definitions reveal a three-way split betweenour word types, the other two contexts produced a two-way splitbetween ambiguous and unambiguous words. These inconsis-tencies align with some discrepancies in behavioural studiesand present a paradox regarding how models learn meaningrelatedness despite natural contexts seemingly lacking suchrelatedness. We argue that viewing ambiguity as a continuumcould resolve many of these issues.