Measuring and Evaluating Syntactic Distance Across Languages Using Universal Dependencies

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AESWSKN4D" target="_blank" >RIV/00216208:11320/26:ESWSKN4D - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1080/09296174.2025.2569581" target="_blank" >http://dx.doi.org/10.1080/09296174.2025.2569581</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/09296174.2025.2569581" target="_blank" >10.1080/09296174.2025.2569581</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Measuring and Evaluating Syntactic Distance Across Languages Using Universal Dependencies

Popis výsledku v původním jazyce

This study addresses the calculation and evaluation of syntactic distance, which is a quantitative measure of structural similarity or divergence between languages. Building on existing alignment-based, feature-based and data-driven approaches, we introduce a novel hypergraph-based metric that assesses syntactic distance through structural alignment while explicitly incorporating word order features. The approach is then applied to a multilingual parallel corpus annotated within the Universal Dependencies (UD) framework, yielding syntactic distances between English and 19 non-English languages. Empirical evaluation further demonstrates the robustness and effectiveness of the proposed measure. Compared with approaches that ablate the hypergraph formalism, ignore word order or rely solely on data-driven metrics, the new metric proves robust under random sampling variation and effectively captures syntactic distance: statistical analyses show that intra-group language pairs exhibit significantly shorter syntactic distances than inter-group pairs. This approach thus provides a novel, formally grounded perspective on language distance based purely on structural properties. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

Název v anglickém jazyce

Measuring and Evaluating Syntactic Distance Across Languages Using Universal Dependencies

Popis výsledku anglicky

This study addresses the calculation and evaluation of syntactic distance, which is a quantitative measure of structural similarity or divergence between languages. Building on existing alignment-based, feature-based and data-driven approaches, we introduce a novel hypergraph-based metric that assesses syntactic distance through structural alignment while explicitly incorporating word order features. The approach is then applied to a multilingual parallel corpus annotated within the Universal Dependencies (UD) framework, yielding syntactic distances between English and 19 non-English languages. Empirical evaluation further demonstrates the robustness and effectiveness of the proposed measure. Compared with approaches that ablate the hypergraph formalism, ignore word order or rely solely on data-driven metrics, the new metric proves robust under random sampling variation and effectively captures syntactic distance: statistical analyses show that intra-group language pairs exhibit significantly shorter syntactic distances than inter-group pairs. This approach thus provides a novel, formally grounded perspective on language distance based purely on structural properties. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

—

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Quantitative Linguistics

ISSN

0929-6174

e-ISSN

—

Svazek periodika

2025

Číslo periodika v rámci svazku

2025

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

22

Strana od-do

1-22

Kód UT WoS článku

001597624200001

EID výsledku v databázi Scopus

2-s2.0-105019711693