An accurate transformer-based model for transition-based dependency parsing of free word order languages

Transformer models are the state-of-the-art in Natural Language Processing (NLP) and the core of the Large Language Models (LLMs). We propose a transformer-based model for transition-based dependency parsing of free word order languages. We have performed experiments on five treebanks from the Unive...

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Autori principali:	Fatima Tuz Zuhra, Khalid Saleem, Surayya Naz
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Springer 2024-07-01
Serie:	Journal of King Saud University: Computer and Information Sciences
Soggetti:	Transformer Free word order languages Static word embeddings Dynamic word embeddings Natural language processing Transition-based dependency parsing
Accesso online:	http://www.sciencedirect.com/science/article/pii/S1319157824001964
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