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

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...

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Publicado en:Language Resources & Evaluation Vol. 59; no. 4; pp. 3445 - 3486
Autores principales: Alzetta, Chiara, Miaschi, Alessio, Dell'Orletta, Felice, Venturi, Giulia, Montemagni, Simonetta
Formato: Artículo
Publicado: Springer Nature Dec2025
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Dec2025
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      pub: Springer Nature
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          Alzetta, Chiara
          Miaschi, Alessio
          Dell'Orletta, Felice
          Venturi, Giulia
          Montemagni, Simonetta
        affil: https://ror.org/028g3pe33 Istituto di Linguistica Computazionale "A. Zampolli", CNR-ILC, ItaliaNLP Lab, via G. Moruzzi 1, Pisa, Italy
      su:
        Syntax (Grammar)
        Transformer models
        Structural linguistics
        Corpora
        Multilingualism
        Language models
      sug:
        subj:
          Syntax (Grammar)
          Transformer models
          Structural linguistics
          Corpora
          Multilingualism
          Language models
      keyword:
        Communication and Culture Linguistics
        Diagnostic probing paradigm
        Language
        Neural language model
        Parallel treebanks
        Syntactic representation
      ab: 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.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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      custom: Language Resources & Evaluation is a copyright of Springer, 2025. All Rights Reserved.
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          year: 2025
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