Chaining and the growth of linguistic categories.

Cognition

Department of Computer Science, Cognitive Science Program, University of Toronto, Canada. Electronic address:

Published: September 2020

We explore how linguistic categories extend over time as novel items are assigned to existing categories. As a case study we consider how Chinese numeral classifiers were extended to emerging nouns over the past half century. Numeral classifiers are common in East and Southeast Asian languages, and are prominent in the cognitive linguistics literature as examples of radial categories. Each member of a radial category is linked to a central prototype, and this view of categorization therefore contrasts with exemplar-based accounts that deny the existence of category prototypes. We explore these competing views by evaluating computational models of category growth that draw on existing psychological models of categorization. We find that an exemplar-based approach closely related to the Generalized Context Model provides the best account of our data. Our work suggests that numeral classifiers and other categories previously described as radial categories may be better understood as exemplar-based categories, and thereby strengthens the connection between cognitive linguistics and psychological models of categorization.

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http://dx.doi.org/10.1016/j.cognition.2020.104323DOI Listing

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