Assessing BERT’s ability to learn Italian syntax: a study on null-subject and agreement phenomena

The work presented in this paper investigates the ability of BERT neural language model pretrained in Italian to embed syntactic dependency relationships into its layers, by approximating a Dependency Parse Tree. To this end, a structural probe, namely a supervised model able to extract linguistic s...

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Bibliographic Details
Published in:	Journal of ambient intelligence and humanized computing Vol. 14; no. 1; pp. 289 - 303
Main Authors:	Guarasci, Raffaele, Silvestri, Stefano, De Pietro, Giuseppe, Fujita, Hamido, Esposito, Massimo
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2023 Springer Nature B.V
Subjects:	Artificial Intelligence Computational Intelligence Engineering English language Italian language Knowledge Linguistics Machine translation Morphology Natural language Original Research Parsers Robotics and Automation Semantics Syntax User Interfaces and Human Computer Interaction Neural language model Structural probe Syntactic phenomena Dependency parse tree
ISSN:	1868-5137, 1868-5145
Online Access:	Get full text
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