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cs.DB2025
A user-friendly SPARQL query editor powered by lightweight metadata
Vincent Emonet, Ana-Claudia Sima, Tarcisio Mendes de Farias
SPARQL query editors often lack intuitive interfaces to aid SPARQL-savvy users to write queries. To address this issue, we propose an easy-to-deploy, triple store-agnostic and open…
cs.DB2025
LLM-based SPARQL Query Generation from Natural Language over Federated Knowledge Graphs
Vincent Emonet, Jerven Bolleman, Severine Duvaud +2
We introduce a Retrieval-Augmented Generation (RAG) system for translating user questions into accurate federated SPARQL queries over bioinformatics knowledge graphs (KGs) leveragi…
cs.DB2024
A large collection of bioinformatics question-query pairs over federated knowledge graphs: methodology and applications
Jerven Bolleman, Vincent Emonet, Adrian Altenhoff +14
Background. In the last decades, several life science resources have structured data using the same framework and made these accessible using the same query language to facilitate…