Managing legal documents, particularly court judgments, can pose a significant challenge due to the extensive and continuously growing volume of involved data. The IDJ platform proposed in this paper aims to tackle this challenge by providing knowledge-driven services designed to enforce the streamlined management of legal documents. The IDJ platform consists of a set of modules, repositories, and data flows that interoperate to realize service pipelines enforcing legal document analytics and exploration processes based on a combination of Natural Language Processing (NLP), machine learning, and syntactic rules. In the paper, we describe two service pipelines enforcing knowledge-driven processes over legal documents, namely the entity-based document analytics, and the concept-based document exploration. A comprehensive experimentation of the proposed knowledge-based service pipelines in a real scenario is finally provided, by considering a corpus repository of Italian court decisions collected in the framework of the Next Generation UPP (NGUPP) digital justice project.

Streamlining Legal Document Management: A Knowledge-Driven Service Platform / V. Bellandi, S. Castano, S. Montanelli, S. Siccardi. - In: SN COMPUTER SCIENCE. - ISSN 2661-8907. - 6:2(2025), pp. 166.1-166.17. [10.1007/s42979-025-03694-y]

Streamlining Legal Document Management: A Knowledge-Driven Service Platform

V. Bellandi
Primo
;
S. Castano
Secondo
;
S. Montanelli
Penultimo
;
S. Siccardi
Ultimo
2025

Abstract

Managing legal documents, particularly court judgments, can pose a significant challenge due to the extensive and continuously growing volume of involved data. The IDJ platform proposed in this paper aims to tackle this challenge by providing knowledge-driven services designed to enforce the streamlined management of legal documents. The IDJ platform consists of a set of modules, repositories, and data flows that interoperate to realize service pipelines enforcing legal document analytics and exploration processes based on a combination of Natural Language Processing (NLP), machine learning, and syntactic rules. In the paper, we describe two service pipelines enforcing knowledge-driven processes over legal documents, namely the entity-based document analytics, and the concept-based document exploration. A comprehensive experimentation of the proposed knowledge-based service pipelines in a real scenario is finally provided, by considering a corpus repository of Italian court decisions collected in the framework of the Next Generation UPP (NGUPP) digital justice project.
Knowledge-driven service platform; Legal concept extraction; Legal entity recognition
Settore INFO-01/A - Informatica
   SEcurity and RIghts in the CyberSpace (SERICS)
   SERICS
   MINISTERO DELL'UNIVERSITA' E DELLA RICERCA
   codice identificativo PE00000014
2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1150795
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