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Ranking task as a tool for studying polysemy: A case study of the Estonian adjective vana ’old’

https://doi.org/10.54013/kk750a3

Keywords: cognitive linguistics, semantics, introspection, experimental methods, multidimensional scaling, facet theory

The aim of the article is to introduce a combination of research methods for studying polysemy. Ranking task is the central tool of this methodological combination, which enables creation of a semantic description that reflects how language users distinguish meanings of the studied word. For introducing the research process I used the Estonian adjective vana ‘old’ as an example. At the beginning of the study, I made the assumption that different senses of the adjective vana are related to different interpretations of time. Introspective analysis of the semantics of the adjective vana included four pairs of opposite time interpretation models. In the ranking task, participants were asked to rank the meanings of vana in different sentences in order of their similarity to the meaning of vana in different reference stimulus sentences. The hypothesis was that those senses of vana which are related to the same time interpretation model would be perceived by participants as being more similar to each other than those which are not related to the same time interpretation model. For analysing the data gathered with the ranking task, I used multidimensional scaling and facet theory. The results of the analysis confirmed the assumption that it is possible to explain the variation of the meaning of the adjective vana on the basis of different interpretations of time. Hence, I concluded that the combination of research methods used here (introspection + ranking task + multidimensional scaling + facet theory) is an appropriate tool for studying polysemy and can be suggested for analysing the semantics of other polysemous words as well.

Aimi Pikksaar (b. 1976), MA, PhD Student at University of Tartu, Institute of Estonian and General Linguistics (Jakobi 2, 51005 Tartu), aimi.pikksaar@ut.ee

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