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The Multidimensional Nature of Semantic Transparency in a Cross-Linguistic Perspective: Evidence From Human
Jing Chen1, Emmanuele Chersoni2, Marco Marelli1
1Department of Psychology, University of Milano - Bicocca.
Cognitive Science
|March 11, 2026
Summary
Semantic transparency in Mandarin Chinese compounds is multidimensional. Different measures capture distinct aspects, influencing word processing and lexical decisions, validating cross-linguistic findings.
Area of Science:
- Psycholinguistics
- Computational Linguistics
- Cognitive Science
Background:
- Semantic transparency is crucial for understanding complex word processing.
- Existing research shows diverse conceptualizations and operationalizations of this construct.
- Cross-linguistic validation is needed to confirm its properties in different languages.
Purpose of the Study:
- To validate the multidimensional properties of semantic transparency in Mandarin Chinese compounds.
- To investigate the latent structure among various measures of semantic transparency.
- To examine the relationship between semantic transparency dimensions and lexical decision performance.
Main Methods:
- Construction of a novel dataset of 2675 Mandarin Chinese nominal compounds.
- Collection of diverse measures: human ratings, traditional distributional semantic models, and large language models.
- Exploratory factor analysis to examine the latent structure of semantic transparency measures.
Main Results:
- Factor analysis confirmed the multidimensional nature of semantic transparency.
- Distinct factors identified: semantic contribution of constituents and predictability of compounds.
- Composite factors predicted lexical decision performance, with second constituent contribution showing a facilitatory effect.
Conclusions:
- The multidimensionality of semantic transparency is extended to Mandarin Chinese compounds.
- Findings support the cross-linguistic validity of the multidimensionality hypothesis.
- The study provides a valuable resource and methodological insights for future research on compound processing.
Keywords:
Compound processingComputational estimatesLarge language modelsMultidimensionalitySemantic transparencyMore Related Videos
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