Wingfield, Cai and Connell, Louise (2022) Understanding the role of linguistic distributional knowledge in cognition. Language, Cognition and Neuroscience, 37 (10). pp. 1220-1270. ISSN 2327-3798

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Abstract

The distributional pattern of words in language forms the basis of linguistic distributional knowledge and contributes to conceptual processing, yet many questions remain regarding its role in cognition. We propose that corpus-based linguistic distributional models can represent a cognitively plausible approach to understanding linguistic distributional knowledge when assumed to represent an essential component of semantics, when trained on corpora representative of human language experience, and when they capture the diverse distributional relations that are useful to cognition. Using an extensive set of cognitive tasks that vary in the complexity of conceptual processing required, we systematically evaluate a wide range of model families, corpora, and parameters, and demonstrate that there is no one-size-fits-all approach for how linguistic distributional knowledge is used across cognition. Rather, linguistic distributional knowledge is a rich source of information about the world that can be accessed flexibly according to the conceptual complexity of the task at hand.

Item Type:	Article
Keywords:	Conceptual processing; linguistic distributional knowledge; distributional semantics; computational modelling;
Academic Unit:	Faculty of Science and Engineering > Psychology
Item ID:	18562
Identification Number:	https://doi.org/10.1080/23273798.2022.2069278
Depositing User:	Louise Connell
Date Deposited:	21 May 2024 15:47
Journal or Publication Title:	Language, Cognition and Neuroscience
Publisher:	Taylor and Francis Group
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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