Parallel Trees: a novel resource with aligned dependency and constituency syntactic representations

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AB9UNUZYC" target="_blank" >RIV/00216208:11320/26:B9UNUZYC - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/s10579-025-09826-3" target="_blank" >http://dx.doi.org/10.1007/s10579-025-09826-3</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10579-025-09826-3" target="_blank" >10.1007/s10579-025-09826-3</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Parallel Trees: a novel resource with aligned dependency and constituency syntactic representations

Popis výsledku v původním jazyce

The paper introduces Parallel Trees, a novel multilingual treebank collection that includes 20 treebanks for 10 languages. The distinguishing property of this resource is that the sentences of each language are annotated using two syntactic representation paradigms (SRPs), respectively based on the notions of dependency and constituency. By aligning the annotations of existing resources, Parallel Trees represents an example of exploiting pre-existing treebanks to adapt them to novel applications. To illustrate its potential, we present a case study where the resource is employed as a benchmark to investigate whether and how BERT, one of the first prominent neural language models (NLMs), is sensitive to the dependency- and constituency-based approaches for representing the syntactic structure of a sentence. The case study results indicate that the model’s sensitivity fluctuates across languages and experimental settings. The unique nature of the Parallel Trees resource creates the prerequisites for innovative studies comparing dependency and phrase-structure trees, allowing for more focused investigations without the interference of lexical variation. © The Author(s) 2025.

Název v anglickém jazyce

Parallel Trees: a novel resource with aligned dependency and constituency syntactic representations

Popis výsledku anglicky

The paper introduces Parallel Trees, a novel multilingual treebank collection that includes 20 treebanks for 10 languages. The distinguishing property of this resource is that the sentences of each language are annotated using two syntactic representation paradigms (SRPs), respectively based on the notions of dependency and constituency. By aligning the annotations of existing resources, Parallel Trees represents an example of exploiting pre-existing treebanks to adapt them to novel applications. To illustrate its potential, we present a case study where the resource is employed as a benchmark to investigate whether and how BERT, one of the first prominent neural language models (NLMs), is sensitive to the dependency- and constituency-based approaches for representing the syntactic structure of a sentence. The case study results indicate that the model’s sensitivity fluctuates across languages and experimental settings. The unique nature of the Parallel Trees resource creates the prerequisites for innovative studies comparing dependency and phrase-structure trees, allowing for more focused investigations without the interference of lexical variation. © The Author(s) 2025.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

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

Language Resources and Evaluation

ISSN

1574-020X

e-ISSN

—

Svazek periodika

2025

Číslo periodika v rámci svazku

2025

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

41

Strana od-do

1-41

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-105009058572