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Article published In: The interface of semantics & etymology, morpho-syntax, and pragmatics in Chinese
Edited by Jeeyoung Peck
[Language and Linguistics 20:2] 2019
► pp. 225–255

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The effect of morphological structure on semantic transparency ratings

 | Shandong University
 | The Hong Kong Polytechnic University
 | The Hong Kong Polytechnic University
 | The Hong Kong Polytechnic University
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Available under the Creative Commons Attribution (CC BY) 4.0 license.

For any use beyond this license, please contact the publisher at rights@benjamins.nl.

Published online: 5 April 2019
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https://doi.org/10.1075/lali.00035.wan
Abstract
Semantic transparency deals with the interface between lexical semantics and morphology. It is an important linguistic phenomenon in Chinese in the context of prediction of meanings of compounds from their constituents. Given prominence of compounding in Chinese morpho-lexical processes, to date there is no semantic transparency dataset available to support verifiable and replicable quantitative analysis of semantic transparency in Mandarin Chinese. In addition, the relation between semantic transparency and morphological structure has not been systematically examined. This paper reports a crowdsourcing-based experiment designed for the construction of a large semantic transparency dataset of Chinese compounds which includes semantic transparency ratings of both the compound and each constituent root of the compound. We also present an analysis of the effects of morphological structure on semantic transparency using the constructed dataset. Our study found that in a transparent modifier-head compound, the head tends to get greater semantic transparency rating than the modifier. Interestingly, no such effect is observed in coordinative compounds. This result suggests that compounds of different morphological structures are processed differently and that the concept of head plays an important role in the word-formation process of compounding. We advocate that crowdsourcing can be a highly instrumental method to collect linguistic judgments and to construct language resources in Chinese language studies. In addition, the proposed methodology of comparing constituent transparency and word transparency sheds light on the relation between morpho-lexical structure and cognitive processing of lexical meanings.
Article outline
  • 1.Introduction
  • 2.Building a semantic transparency dataset
    • 2.1Method
      • 2.1.1Materials
      • 2.1.2Questionnaires and data quality assurance
      • 2.1.3Quality control in crowdsourcing
      • 2.1.4Platform and procedure
    • 2.2Results
      • 2.2.1Data cleaning and result calculation
      • 2.2.2Evaluation
        • 2.2.2.1Intra-group consistency
          • Intra-group consistency of OST scores
          • Intra-group consistency of CST scores
        • 2.2.2.2Inter-group consistency
        • 2.2.2.3Correlation between OST and CST results
      • 2.2.3Merging and normalization
      • 2.2.4Distribution and classification
    • 2.3Correlations with laboratory experimental results
  • 3.Testing morphological structure effect on semantic transparency ratings
    • 3.1Method
    • 3.2Results
      • 3.2.1Testing prediction 1
      • 3.2.2Testing prediction 2
      • 3.2.3Resampling simulation analysis
  • 4.General discussion and conclusion
  • Acknowledgements
  • Notes
  • Abbreviations
  • References
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