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...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Journal of ambient intelligence and humanized computing Ročník 14; číslo 1; s. 289 - 303
Hlavní autori:	Guarasci, Raffaele, Silvestri, Stefano, De Pietro, Giuseppe, Fujita, Hamido, Esposito, Massimo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2023 Springer Nature B.V
Predmet:	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
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!