Principles of semantic and functional efficiency in grammatical patterning
Emily Cheng, Francesca Franzon

TL;DR
This paper proposes an information-theoretic framework explaining universal grammatical patterns as a balance between semantic encoding and processing efficiency, supported by analyses across diverse languages.
Contribution
It unifies semantic encoding and agreement predictability into a single model, explaining the organization of grammatical features across languages based on cognitive constraints.
Findings
Grammatical patterns are rooted in perceptual attributes.
Languages prioritize processing efficiency over semantic encoding.
The model accounts for universal grammatical organization.
Abstract
Grammatical features such as number and gender serve two central functions in human languages. While they encode salient semantic attributes like numerosity and animacy, they also offload sentence processing cost by predictably linking words together via grammatical agreement. Grammars exhibit consistent organizational patterns across diverse languages, invariably rooted in a semantic foundation-a widely confirmed but still theoretically unexplained phenomenon. To explain the basis of universal grammatical patterns, we unify two fundamental properties of grammar, semantic encoding and agreement-based predictability, into a single information-theoretic objective under cognitive constraints, accounting for variable communicative need. Our analyses reveal that grammatical organization provably inherits from perceptual attributes, and our measurements on a diverse language sample show that…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsPhonetics and Phonology Research · Natural Language Processing Techniques · Syntax, Semantics, Linguistic Variation
