Modelling meaning composition from formalism to mechanism.

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ID: 84775
2020
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Abstract
Human thought and language have extraordinary expressive power because meaningful parts can be assembled into more complex semantic structures. This partly underlies our ability to compose meanings into endlessly novel configurations, and sets us apart from other species and current computing devices. Crucially, human behaviour, including language use and linguistic data, indicates that composing parts into complex structures does not threaten the existence of constituent parts as independent units in the system: parts and wholes exist simultaneously yet independently from one another in the mind and brain. This independence is evident in human behaviour, but it seems at odds with what is known about the brain's exquisite sensitivity to statistical patterns: everyday language use is productive and expressive precisely because it can go beyond statistical regularities. Formal theories in philosophy and linguistics explain this fact by assuming that language and thought are : systems of representations that separate a variable (or ) from its values (), such that the meaning of a complex expression is a function of the values assigned to the variables. The debate on whether and how compositional systems could be implemented in minds, brains and machines remains vigorous. However, it has not yet resulted in mechanistic models of semantic composition: how, then, are the constituents of thoughts and sentences put and held together? We review and discuss current efforts at understanding this problem, and we chart possible routes for future research. This article is part of the theme issue 'Towards mechanistic models of meaning composition'.
Reference Key
martin2020modellingphilosophical Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Martin, Andrea E;Baggio, Giosuè;
Journal philosophical transactions of the royal society of london series b, biological sciences
Year 2020
DOI
10.1098/rstb.2019.0298
URL
Keywords
semantics cognition language neuroscience compositionality mechanistic models

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