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Modelling meaning composition from formalism to mechanism.

Andrea E Martin1,2, Giosuè Baggio3

  • 1Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
|December 17, 2019
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Summary

Human language and thought achieve expressive power through semantic composition, allowing novel meanings while preserving constituent parts. Mechanistic models are needed to explain how the brain achieves this complex compositional system.

Keywords:
cognitioncompositionalitylanguagemechanistic modelsneurosciencesemantics

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Area of Science:

  • Cognitive Science
  • Neuroscience
  • Linguistics

Background:

  • Human language and thought exhibit remarkable expressive power through the assembly of meaningful parts into complex semantic structures.
  • This compositional ability allows for novel meaning creation, distinguishing humans from other species and current AI.
  • Linguistic data suggests that constituent parts remain independent within the system, existing simultaneously with complex wholes.

Discussion:

  • The brain's sensitivity to statistical patterns appears at odds with the productive and expressive nature of language, which often transcends regularities.
  • Formal theories propose compositional systems in language and thought, separating variables (roles) from their values (fillers).
  • The debate on implementing compositional systems in minds, brains, and machines continues, lacking mechanistic models.

Key Insights:

  • Human cognition and language are compositional, enabling the creation of complex meanings from simpler components.
  • The independence of parts and wholes in semantic structures is a key characteristic of human thought and language.
  • Current research faces challenges in developing mechanistic models for semantic composition.

Outlook:

  • Future research should focus on developing mechanistic models to explain how semantic composition is implemented in the brain.
  • Investigating the interplay between statistical learning and compositional processes is crucial.
  • Bridging formal theories with neurobiological evidence will advance our understanding of meaning composition.