LLM-based SPARQL Query Generation from Natural Language over Federated Knowledge Graphs
<|reference_start|>LLM-based SPARQL Query Generation from Natural Language over Federated Knowledge Graphs: We introduce a Retrieval-Augmented Generation (RAG) system for translating user questions into accurate federated SPARQL queries over bioinformatics knowledge graphs (KGs) leveraging Large Language Models (LLMs). To enhance accuracy and reduce hallucinations in query generation, our system utilises metadata from the KGs, including query examples and schema information, and incorporates a validation step to correct generated queries. The system is available online at chat.expasy.org.<|reference_end|>
@article{emonet2024llm-based,
    title={LLM-based SPARQL Query Generation from Natural Language over Federated
  Knowledge Graphs},
    author={Vincent Emonet, Jerven Bolleman, Severine Duvaud, Tarcisio Mendes de
  Farias and Ana Claudia Sima},
    journal={arXiv preprint arXiv:2410.06062},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.06062},
    primaryClass={cs.DB cs.AI cs.IR}
}