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Updated: May 29, 2025

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Composition as Nonlinear Combination in Semantic Space: A Computational Characterization of Compound Processing.

Tianqi Wang1,2, Xu Xu1

  • 1School of Foreign Languages, Shanghai Jiao Tong University.

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Summary
This summary is machine-generated.

Chinese compound words

Keywords:
Chinese morphologyCompound word processingDistributional semantic modelsDual‐route modelLexical decisionSentence reading

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Area of Science:

  • Computational linguistics
  • Cognitive science
  • Psycholinguistics

Background:

  • Most Chinese words are compounds formed by combining meaningful characters.
  • The process of how this compositionality affects whole-word meaning access is not well understood.
  • Compositional complexity poses challenges in understanding word meaning.

Purpose of the Study:

  • To investigate the combinatorial process in Chinese compound word comprehension.
  • To explore the relationship between constituent characters and compound word meaning using computational methods.
  • To provide a computational characterization of the dual-route framework for compound processing.

Main Methods:

  • Employed a deep neural network to learn character-word relationships.
  • Utilized compositional distributional semantics to derive word representations.
  • Analyzed lexical decision and eye-tracking data.

Main Results:

  • Compositional attributes significantly influenced compound processing, beyond constituent and whole-word features.
  • The influence of compositional attributes decreased as compound frequency increased.
  • Findings suggest an active engagement of the combinatorial process in word comprehension.

Conclusions:

  • The study provides computational evidence for the dual-route framework in compound processing.
  • Highlights the interplay between compositional and holistic processing routes.
  • Offers insights into the universal mechanisms of compound comprehension across languages.