This paper describes a pipeline for data management, knowledge extraction and semantic analysis of unstructured legal judgments on a digital database. The research focuses on the storage of judgments, the processing of textual content through the use of Natural Language Processing and AI technologies and the advanced semantic navigation of the database. These results are obtained from the research group of the University of Torino in the NGUPP project.

A pipeline for data management, knowledge extraction and semantic analysis of unstructured legal judgments

Chiara Bonfanti
;
Michele Colombino;Giorgia Iacobellis;Rachele Mignone;Ivan Spada;Laurentiu Jr Marius Zaharia;Marinella Quaranta;Marianna Molinari;Susanna Marta;Ilaria Angela Amantea;Davide Audrito;Emilio Sulis;Luigi Di Caro;Guido Boella
2023-01-01

Abstract

This paper describes a pipeline for data management, knowledge extraction and semantic analysis of unstructured legal judgments on a digital database. The research focuses on the storage of judgments, the processing of textual content through the use of Natural Language Processing and AI technologies and the advanced semantic navigation of the database. These results are obtained from the research group of the University of Torino in the NGUPP project.
2023
AI per la Pubblica Amministrazione
Pisa, Italy
May 29-30
Proceedings of the Italia Intelligenza Artificiale - Thematic Workshops co-located with the 3rd CINI National Lab AIIS Conference on Artificial Intelligence (Ital IA 2023)
CEUR
229
234
Legal informatics, Legal document classification, Legal document similarity, Principles of Law, Text embeddings
Chiara Bonfanti, Michele Colombino, Giorgia Iacobellis, Rachele Mignone, Ivan Spada, Laurentiu Jr Marius Zaharia, Marinella Quaranta, Marianna Molinari, Susanna Marta, Ilaria Angela Amantea, Davide Audrito, Emilio Sulis, Luigi Di Caro, Guido Boella
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1945623
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