Rethinking and formalising the state across languages: a unified computational learning theory account

Abstract:The linguistic notion of state has traditionally been restricted to the construct (annexation) state of Afroasiatic languages and treated as a language-specific morphosyntactic phenomenon. This article argues instead that the state is a systemic, context-dependent morphosyntactic mechanism that selects grammatical templates across synthetic languages. Within the Template-Based Modular Cognitive framework, taking Riffian as its primary empirical basis, the proposed theory provides a unified explanation for diverse nominal marking patterns traditionally analysed independently and is formalised as a symbolic computational model in which the state is represented by a set-valued function over grammatical templates. A learning algorithm based on finite-set operations acquires and predicts state-dependent grammatical configurations. Beyond nominal morphology, the framework has broader implications for theories of nominal structure and lexical cognition, in particular offering a unified analysis of determiner-noun structure. These results suggest that the state constitutes one instance of a broader class of syntactically conditioned dependencies that also includes agreement and grammatical case.

Computation and Language (cs.CL); Artificial Intelligence (cs.AI)

arXiv:2608.00523 [cs.CL]

(or arXiv:2608.00523v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2608.00523 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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