The Multidimensional Nature of Semantic Transparency in a Cross‐Linguistic Perspective: Evidence From Human Intuitions, Computational Estimates, and Processing Data for Chinese Compounds
Jing Chen, Emmanuele Chersoni, Marco Marelli, Chu‐Ren Huang
TL;DR
This study explores how semantic transparency in Chinese compounds can be understood through multiple dimensions using human ratings and computational models.
Contribution
The study validates the multidimensionality of semantic transparency in Mandarin Chinese compounds using a novel dataset and factor analysis.
Findings
Semantic transparency in Chinese compounds is multidimensional, with distinct factors for constituent contribution and compound predictability.
The second constituent's semantic contribution significantly affects lexical decision performance.
The findings extend the multidimensionality hypothesis of semantic transparency to Chinese compounds.
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…
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Taxonomy
TopicsNeurobiology of Language and Bilingualism · Categorization, perception, and language · Language, Metaphor, and Cognition