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Can syntax swallow semantics? Or might it not be the other way around?

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Published/Copyright: March 19, 2025
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Folia Linguistica
From the journal Folia Linguistica

Abstract

In the Generative model of human language, the semantic component has the role of interpreting the syntax. This amounts to semantics being swallowed up by syntax and explains Chomsky’s reiterated statements that at bottom natural language has only syntax and pragmatics: “natural language has no semantics … it has syntax (symbol manipulation) and pragmatics (modes of use of language)” (Chomsky, Noam. 2013. Notes on denotation and denoting. In Ivano Caponigro & Carlo Conchetto (eds.), From grammar to meaning: the spontaneous logicality of language, 38–45. Cambridge: Cambridge University Press). It will be argued that this conclusion is predetermined by the view of language as a computationally perfect syntactic system. Language is thereby reduced to syntactic distribution and symbol manipulation, linguistic form separated from meaning, with syntax being investigated according to the goals of coherence and consistency and subsequently reconnected extrinsically to the world by means of pragmatics. It will be shown that a basic understanding of the nature of language, which is constituted by the fundamental correlation between linguistic signs and their meanings, reveals that one cannot isolate and study separately the physically observable side of language without tearing asunder the very object of one’s investigation. The causal conditioning of syntax by both semantics and pragmatics will be demonstrated via the examples of English causative verbs and the ‘degree adverb + proper name’ construction.


Corresponding author: Patrick Duffley, Département de langues, linguistique et traduction, Université Laval, 1030, avenue des Sciences-Humaines, Québec, QC, G1V 0A6, Canada, E-mail:

  1. Research ethics: N/A.

  2. Informed consent: N/A.

  3. Author contributions: The author has accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: No.

  5. Conflict of interest: No.

  6. Research funding: None.

  7. Data availability: N/A.

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Received: 2024-10-09
Accepted: 2025-02-23
Published Online: 2025-03-19

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