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This article investigates the universal structural properties of syntactic dependency trees across 124 languages, proposing that they emerge from incremental grammatical encoding via sublinear preferential attachment rather than direct optimization for communication. By modeling these patterns as a cognitively motivated generative process, the study offers insights into how efficient linguistic structures arise naturally without explicit design.
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Universal Topological Regularity of Syntactic Structures

arXiv2 min read

arXiv:2302.00129v2 Announce Type: replace Abstract: Despite their widespread use, the principles governing the organisation of syntactic dependency trees remain poorly understood. I analyse dependency trees from 124 typologically, genetically, and geographically diverse languages. Their topology departs systematically from randomness. Relative to uniformly sampled random trees, dependency trees exhibit greater structural robustness and lower branching heterogeneity. I propose that these universal regularities emerge naturally from incremental grammatical encoding. I model this process using sublinear preferential attachment. The model accurately reproduces the observed topology. More generally, the results demonstrate how a universal statistical property of syntax can emerge from a simple, cognitively motivated generative process. They further illustrate a broader principle of efficiency by construction: communicatively efficient syntactic structures can emerge without direct optimisation for communication.

Abstract:Despite their widespread use, the principles governing the organisation of syntactic dependency trees remain poorly understood. I analyse dependency trees from 124 typologically, genetically, and geographically diverse languages. Their topology departs systematically from randomness. Relative to uniformly sampled random trees, dependency trees exhibit greater structural robustness and lower branching heterogeneity. I propose that these universal regularities emerge naturally from incremental grammatical encoding. I model this process using sublinear preferential attachment. The model accurately reproduces the observed topology. More generally, the results demonstrate how a universal statistical property of syntax can emerge from a simple, cognitively motivated generative process. They further illustrate a broader principle of efficiency by construction: communicatively efficient syntactic structures can emerge without direct optimisation for communication.

Computation and Language (cs.CL); Neurons and Cognition (q-bio.NC)

arXiv:2302.00129 [cs.CL]

(or arXiv:2302.00129v2 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2302.00129 Focus to learn more arXiv-issued DOI via DataCite

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Full text under the publisher's open licence · 216 words

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