LLM-based SPARQL Query Generation from Natural Language over Federated Knowledge Graphs
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866916605411196928 |
|---|---|
| author | Emonet, Vincent Bolleman, Jerven Duvaud, Severine de Farias, Tarcisio Mendes Sima, Ana Claudia |
| author_facet | Emonet, Vincent Bolleman, Jerven Duvaud, Severine de Farias, Tarcisio Mendes Sima, Ana Claudia |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_06062 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | LLM-based SPARQL Query Generation from Natural Language over Federated Knowledge Graphs Emonet, Vincent Bolleman, Jerven Duvaud, Severine de Farias, Tarcisio Mendes Sima, Ana Claudia Databases Artificial Intelligence Information Retrieval 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. |
| title | LLM-based SPARQL Query Generation from Natural Language over Federated Knowledge Graphs |
| topic | Databases Artificial Intelligence Information Retrieval |
| url | https://arxiv.org/abs/2410.06062 |