Knowledge Graphs Construction from Criminal Court Appeals: Insights from the French Cassation Court
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866909465475809280 |
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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 |