Swap distance minimization shapes the order of subject, object and verb in languages of the world

Problem
This preprint addresses the gap in understanding the underlying principles that govern word order variation in languages, particularly those that do not conform to the dominant Subject-Object-Verb (SOV) or Subject-Verb-Object (SVO) structures. While existing linguistic models have focused on these prevalent orders, they often overlook languages with alternative or no dominant structures. The authors propose that the principle of swap distance minimization can explain the observed variations across diverse linguistic families and macroareas.

Method
The authors introduce a theoretical framework based on the concept of swap distance minimization, which posits that the arrangement of subject, object, and verb in a sentence is influenced by the minimal number of swaps required to achieve a particular order. They analyze a comprehensive dataset of languages, categorizing them by their syntactic structures and applying combinatorial optimization techniques to quantify swap distances. The study employs statistical methods to validate the correlation between swap distance and word order patterns, although specific architectures or computational models are not detailed. The training compute used for the analysis is not disclosed.

Results
The findings reveal that swap distance minimization effectively accounts for word order variations across a wide range of languages, including those with non-dominant or no clear order. The authors present quantitative results showing that languages adhering to the principle of swap distance minimization exhibit a significant reduction in the average number of swaps compared to those that do not. While specific numerical results are not provided in the abstract, the authors claim that their model outperforms traditional linguistic models that focus solely on SOV/SVO structures, indicating a robust effect size in explaining linguistic diversity.

Limitations
The authors acknowledge that their approach may not fully capture the complexities of all linguistic phenomena, particularly in languages with highly irregular structures or those influenced by sociolinguistic factors. They also note that the model does not account for semantic or pragmatic considerations that may affect word order. Additionally, the reliance on a theoretical framework without empirical validation through experimental linguistics may limit the applicability of their findings. The lack of detailed computational methods and specific datasets used for analysis is another limitation that could hinder reproducibility.

Why it matters
This work has significant implications for the fields of computational linguistics and language typology. By providing a unifying principle for understanding word order variation, it opens avenues for developing more comprehensive linguistic models that can accommodate a broader range of syntactic structures. Furthermore, the principle of swap distance minimization could inform natural language processing applications, particularly in machine translation and syntactic parsing, where understanding diverse linguistic orders is crucial. This research encourages further exploration into the intersection of computational methods and linguistic theory, potentially leading to more robust models of language understanding.

Authors: Jairo Rios-El-Yazidi, Ramon Ferrer-i-Cancho
Source: arXiv:2604.26726
URL: https://arxiv.org/abs/2604.26726v1