Back to Search Start Over

Decomposing unaccusativity: a statistical modelling approach.

Authors :
Kim, Songhee
Binder, Jeffrey R.
Humphries, Colin
Conant, Lisa L.
Source :
Language, Cognition & Neuroscience. Nov2024, Vol. 39 Issue 9, p1189-1211. 23p.
Publication Year :
2024

Abstract

While the two types of intransitive verbs, i.e. unergative and unaccusative, are hypothesised to be syntactically represented, many have proposed a semantic account where abstract properties related to agentivity and telicity, often conceptualised as binary properties, determine the classification. Here we explore the extent to which graded, embodied features rooted in neurobiological systems contribute to the distinction, representing verb meanings as continuous human ratings over various experiential dimensions. Unlike prior studies that classified verbs based on categorical intuition, we assessed the degree of unaccusativity by acceptability of the prenominal past participle construction, one of the unaccusativity diagnostics. Five models were constructed to explain these data: categorical syntactic/semantic, feature-based event-semantic, experiential, and distributional models. The experiential model best explained the diagnostic test data, suggesting that the unaccusative/unergative distinction may be an emergent phenomenon related to differences in underlying experiential content. The experiential model's advantages, including interpretability and scalability, are also discussed. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23273798
Volume :
39
Issue :
9
Database :
Academic Search Index
Journal :
Language, Cognition & Neuroscience
Publication Type :
Academic Journal
Accession number :
180278796
Full Text :
https://doi.org/10.1080/23273798.2024.2368119