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Bibliographic Details
Main Authors: Belikov, Alexander V., Raoult, Sacha
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2501.14579
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author Belikov, Alexander V.
Raoult, Sacha
author_facet Belikov, Alexander V.
Raoult, Sacha
contents Despite growing interest, accurately and reliably representing unstructured data, such as court decisions, in a structured form, remains a challenge. Recent advancements in generative AI applied to language modeling enabled the transformation of text into knowledge graphs, unlocking new opportunities for analysis and modeling. This paper presents a framework for constructing knowledge graphs from appeals to the French Cassation Court. The framework includes a domain-specific ontology and a derived dataset, offering a foundation for structured legal data representation and analysis.
format Preprint
id arxiv_https___arxiv_org_abs_2501_14579
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Knowledge Graphs Construction from Criminal Court Appeals: Insights from the French Cassation Court
Belikov, Alexander V.
Raoult, Sacha
Information Retrieval
Despite growing interest, accurately and reliably representing unstructured data, such as court decisions, in a structured form, remains a challenge. Recent advancements in generative AI applied to language modeling enabled the transformation of text into knowledge graphs, unlocking new opportunities for analysis and modeling. This paper presents a framework for constructing knowledge graphs from appeals to the French Cassation Court. The framework includes a domain-specific ontology and a derived dataset, offering a foundation for structured legal data representation and analysis.
title Knowledge Graphs Construction from Criminal Court Appeals: Insights from the French Cassation Court
topic Information Retrieval
url https://arxiv.org/abs/2501.14579