The distribution of syntactic dependency distances
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AMKQZUFWU" target="_blank" >RIV/00216208:11320/26:MKQZUFWU - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.53482/2025_58_424" target="_blank" >http://dx.doi.org/10.53482/2025_58_424</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.53482/2025_58_424" target="_blank" >10.53482/2025_58_424</a>
Alternative languages
Result language
angličtina
Original language name
The distribution of syntactic dependency distances
Original language description
The syntactic structure of a sentence can be represented as a graph, where vertices are words and edges indicate syntactic dependencies between them. In this setting, the distance between two linked words is defined as the difference between their positions. Here we wish to contribute to the characterization of the actual distribution of syntactic dependency distances, which has previously been argued to follow a power-law distribution. Here we propose a new model with two exponential regimes in which the probability decay is allowed to change after a break-point. This transition could mirror the transition from the processing of word chunks to higher-level structures. We find that a two-regime model – where the first regime follows either an exponential or a power-law decay – is the most likely one in all 20 languages we considered, independently of sentence length and annotation style. Moreover, the break-point exhibits low variation across languages and averages values of 4-5 words, suggesting that the amount of words that can be simultaneously processed abstracts from the specific language to a high degree. The probability decay slows down after the breakpoint, consistently with a universal chunk-and-pass mechanism. Finally, we give an account of the relation between the best estimated model and the closeness of syntactic dependencies as function of sentence length, according to a recently introduced optimality score. © 2025, International Quantitative Linguistics Association. All rights reserved.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Glottometrics
ISSN
1617-8351
e-ISSN
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Volume of the periodical
58
Issue of the periodical within the volume
2025
Country of publishing house
US - UNITED STATES
Number of pages
60
Pages from-to
35-94
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-105013295380