Universal Topological Regularities of Syntactic Structures: Decoupling Efficiency from Optimization

Fermín Moscoso del Prado Martín
1/31/2023
cs.CLq-bio.NC

No confident code implementation found for this paper.

Abstract

Human syntactic structures are usually represented as graphs. Much research has focused on the mapping between such graphs and linguistic sequences, but less attention has been paid to the shapes of the graphs themselves: their topologies. This study investigates how the topologies of syntactic graphs reveal traces of the processes that led to their emergence. I report a new universal regularity in syntactic structures: Their topology is communicatively efficient above chance. The pattern holds, without exception, for all 124 languages studied, across linguistic families and modalities (spoken, written, and signed). This pattern can arise from a process optimizing for communicative efficiency or, alternatively, by construction, as a by-effect of a sublinear preferential attachment process reflecting language production mechanisms known from psycholinguistics. This dual explanation shows how communicative efficiency, per se, does not require optimization. Among the two options, efficiency without optimization offers the better explanation for the new pattern.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{martn2023universal,
  title  = {Universal Topological Regularities of Syntactic Structures: Decoupling Efficiency from Optimization},
  author = {Fermín Moscoso del Prado Martín},
  year   = {2023},
  eprint = {2302.00129},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2302.00129v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2302.00129.svg)](https://codeofpaper.com/paper/2302.00129)

Discussion