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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Martim Zanatti, Ribeiro, R. & Pinto, H. Sofia (2025). Segmentation Model for Judgments of the Portuguese Supreme Court of Justice. In Progress in Artificial Intelligence. EPIA 2024. Lecture Notes in Computer Science, vol 14969. (pp. 245-257). Viana do Castelo: Springer.
Exportar Referência (IEEE) 
M. Zanatti et al.,  "Segmentation Model for Judgments of the Portuguese Supreme Court of Justice", in Progress in Artificial Intelligence. EPIA 2024. Lecture Notes in Computer Science, vol 14969, Viana do Castelo, Springer, 2025, pp. 245-257
Exportar BibTeX 
@inproceedings{zanatti2025_1777775097684,
	author = "Martim Zanatti and Ribeiro, R. and Pinto, H. Sofia",
	title = "Segmentation Model for Judgments of the Portuguese Supreme Court of Justice",
	booktitle = "Progress in Artificial Intelligence. EPIA 2024. Lecture Notes in Computer Science, vol 14969",
	year = "2025",
	editor = "",
	volume = "",
	number = "",
	series = "",
	doi = "10.1007/978-3-031-73497-7_20",
	pages = "245-257",
	publisher = "Springer",
	address = "Viana do Castelo",
	organization = "APPIA",
	url = "https://link.springer.com/chapter/10.1007/978-3-031-73497-7_20"
}
Exportar RIS 
TY  - CPAPER
TI  - Segmentation Model for Judgments of the Portuguese Supreme Court of Justice
T2  - Progress in Artificial Intelligence. EPIA 2024. Lecture Notes in Computer Science, vol 14969
AU  - Martim Zanatti
AU  - Ribeiro, R.
AU  - Pinto, H. Sofia
PY  - 2025
SP  - 245-257
DO  - 10.1007/978-3-031-73497-7_20
CY  - Viana do Castelo
UR  - https://link.springer.com/chapter/10.1007/978-3-031-73497-7_20
AB  - Legal document segmentation is a critical task in the field of natural language processing (NLP), enabling efficient analysis, retrieval, and understanding of legal content. Despite its importance, research in this area for European Portuguese has been limited. To address this gap, we present a novel approach to automate the segmentation of legal judgments from the Portuguese Supreme Court of Justice into distinct sections. Leveraging a Bi-LSTM-CRF model, we developed a dataset and achieved significant results, including an accuracy of 0.9997, precision of 0.9986, recall of 0.996, and F1-Score of 0.9973. Our methodology and experimental results demonstrate the effectiveness and potential applications of our approach for the European Portuguese language.
ER  -