D4R -- Exploring and Querying Relational Graphs Using Natural Language and Large Language Models -- the Case of Historical Documents

March 26, 2025 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Michel Boeglin, David Kahn, Josiane Mothe, Diego Ortiz, David Panzoli arXiv ID 2503.20914 Category cs.IR: Information Retrieval Cross-listed cs.AI, cs.CL, cs.LG Citations 0 Venue arXiv.org Last Checked 4 months ago
Abstract
D4R is a digital platform designed to assist non-technical users, particularly historians, in exploring textual documents through advanced graphical tools for text analysis and knowledge extraction. By leveraging a large language model, D4R translates natural language questions into Cypher queries, enabling the retrieval of data from a Neo4J database. A user-friendly graphical interface allows for intuitive interaction, enabling users to navigate and analyse complex relational data extracted from unstructured textual documents. Originally designed to bridge the gap between AI technologies and historical research, D4R's capabilities extend to various other domains. A demonstration video and a live software demo are available.
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