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The Multidimensional Nature of Semantic Transparency in a Cross-Linguistic Perspective: Evidence From Human Intuitions, Computational Estimates, and Processing Data for Chinese Compounds.

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Title: The Multidimensional Nature of Semantic Transparency in a Cross-Linguistic Perspective: Evidence From Human Intuitions, Computational Estimates, and Processing Data for Chinese Compounds.
Authors: Chen J; Department of Psychology, University of Milano - Bicocca., Chersoni E; Department of Language Science and Technology, The Hong Kong Polytechnic University., Marelli M; Department of Psychology, University of Milano - Bicocca., Huang CR; Department of Language Science and Technology, The Hong Kong Polytechnic University.
Source: Cognitive science [Cogn Sci] 2026 Mar; Vol. 50 (3), pp. e70194.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Language: English
Journal Info: Publisher: Wiley-Blackwell Country of Publication: United States NLM ID: 7708195 Publication Model: Print Cited Medium: Internet ISSN: 1551-6709 (Electronic) Linking ISSN: 03640213 NLM ISO Abbreviation: Cogn Sci Subsets: MEDLINE
Imprint Name(s): Publication: 2009-: Hoboken, N.J. : Wiley-Blackwell
Original Publication: Norwood, N. J., Ablex Pub. Corp.
MeSH Terms: Language* , Linguistics* , Psycholinguistics* , Semantics*, Adult ; Female ; Humans ; Male ; Young Adult ; China
Abstract: Semantic transparency is a key construct for understanding how complex words are represented and processed, yet it has been conceptualized and operationalized in diverse ways across studies. In this study, we validate whether semantic transparency exhibits multidimensional properties across different measures in Mandarin Chinese. We first construct a novel dataset consisting of 2675 nominal compounds, with a rich set of measures from human ratings, traditional distributional semantic models, and recent large language models. To investigate whether they inform the same aspects of this construct, we then examine the latent structure among these measures through exploratory factor analysis. Our factor analysis reveals that this construct is fundamentally multidimensional, with measures assessing the semantic contribution of each constituent and the semantic predictability of overall compounds representing distinct factors in the latent structure. These derived composite factors also predict lexical decision performance, with the factor representing second constituent contribution showing significant facilitatory effects. Our work extends the cross-linguistic validity of the multidimensionality hypothesis of this theoretical construct previously established in English and German to Chinese compounds. Additionally, we provide a valuable resource for future research on the representation and processing of compounds, together with methodological insights into using computational estimates to augment psycholinguistic datasets across dimensions of semantic transparency.
(© 2026 The Author(s). Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)
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Grant Information: PolyU 15612222 Research Grants Council of the Hong Kong Special Administrative Region, China; 1-BE8G Faculty of Humanities, The Hong Kong Polytechnic University
Contributed Indexing: Keywords: Compound processing; Computational estimates; Large language models; Multidimensionality; Semantic transparency
Entry Date(s): Date Created: 20260311 Date Completed: 20260311 Latest Revision: 20260813
Update Code: 20260813
PubMed Central ID: PMC12976469
DOI: 10.1111/cogs.70194
PMID: 41808299
Database: MEDLINE
Description
ISSN:1551-6709
DOI:10.1111/cogs.70194