Although with some discrepancy, both in common law and in civil law systems, previous judgments play an important role with respect to future decisions. Traditional legal methodologies usually involve the use of manual rather than automatic keyword search mechanisms to retrace the steps of the judicial decision-making. However, these methods are generally highly time-consuming and can be subject to different types of biases. In this work, we present an automated extraction pipeline to map and structure citations in rulings regarding fiscal state aids in the case-law of the Court of Justice of the European Union. In particular, by exploiting the available XML data in the EUR-Lex platform, we built an end-to-end parser based on a set of regular expressions and heuristics, which is able to iteratively extract all citations, finally creating a hierarchical structure of citations with their contextual information at the paragraph level. Such data structure can be projected into a graphical representation, enabling useful visualization and exploration features and insights, such as the diachronic study of the development of specific citations and legal principles over time. Our work suggests how the exploitation and analysis of citation networks through automated means can provide significant tools to support traditional legal methodologies.

Automated Extraction and Representation of Citation Network: A CJEU Case-Study

Sartor G.;Santin P.;Audrito D.;Sulis E.;Di Caro L.
2022-01-01

Abstract

Although with some discrepancy, both in common law and in civil law systems, previous judgments play an important role with respect to future decisions. Traditional legal methodologies usually involve the use of manual rather than automatic keyword search mechanisms to retrace the steps of the judicial decision-making. However, these methods are generally highly time-consuming and can be subject to different types of biases. In this work, we present an automated extraction pipeline to map and structure citations in rulings regarding fiscal state aids in the case-law of the Court of Justice of the European Union. In particular, by exploiting the available XML data in the EUR-Lex platform, we built an end-to-end parser based on a set of regular expressions and heuristics, which is able to iteratively extract all citations, finally creating a hierarchical structure of citations with their contextual information at the paragraph level. Such data structure can be projected into a graphical representation, enabling useful visualization and exploration features and insights, such as the diachronic study of the development of specific citations and legal principles over time. Our work suggests how the exploitation and analysis of citation networks through automated means can provide significant tools to support traditional legal methodologies.
2022
3rd International Workshop on Conceptual Modeling for Life Sciences, CMLS 2022, 5th International Workshop on Empirical Methods in Conceptual Modeling, EmpER 2022, 1st International Workshop on Digital Justice, Digital Law and Conceptual Modeling, JUSMOD 2022 held at 41st International Conference on Conceptual Modeling, ER 2022
Online (Virtual)
2022
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Springer Science and Business Media Deutschland GmbH
13650
102
111
9783031220357
9783031220364
Citation network; Digital justice; Legal knowledge extraction; Visual law
Sartor G.; Santin P.; Audrito D.; Sulis E.; Di Caro L.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2122349
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