Please use this identifier to cite or link to this item:
http://hdl.handle.net/10174/39472
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| Title: | Assessing European and Brazilian Portuguese LLMs for NER in Specialised Domains |
| Authors: | Nunes, Rafael
Santos, Joaquim
Balreira, Dennis
Freitas, Carla
Olival, Fernanda
Cameron, Helena
Vieira, Renata |
| Keywords: | Named entity recognition
Portuguese language variants |
| Issue Date: | Jan-2025 |
| Publisher: | Springer Nature |
| Citation: | Nunes, R.O. et al. (2025). Assessing European and Brazilian Portuguese LLMs for NER in Specialised Domains. In: Paes, A., Verri, F.A.N. (eds) Intelligent Systems. BRACIS 2024. Lecture Notes in Computer Science(), vol 15412. Springer, Cham. https://doi.org/10.1007/978-3-031-79029-4_15 |
| Abstract: | This paper discusses the impact of Portuguese variants in Large Language Models for the task of named entity recognition (NER) in specialised domains. The tests were made on a Brazilian Portuguese legal and a European Portuguese historical corpora. The models taken into account are BERTimbau (PT-BR), Albertina (PT-PT and PT-BR), and XML-R (multilingual). The impact was more evident in the Portuguese historical corpus, which resulted in higher F1 measures compared to previous works that did not consider the same language variant. Additionally, the study underscores the impact of model architecture on performance, highlighting the critical role of both linguistic alignment and model size in enhancing NER in specialised domains. |
| URI: | https://link.springer.com/chapter/10.1007/978-3-031-79029-4_15#citeas
http://hdl.handle.net/10174/39472 |
| Type: | bookPart |
| Appears in Collections: | CIDEHUS - Publicações - Capítulos de Livros
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