Large Language Models ↔ SPARQL

Relations (1)

related 2.32 — strongly supporting 4 facts

Large Language Models are related to SPARQL because they are frequently used to generate SPARQL queries to retrieve information from knowledge graphs, as described in [1] and [2]. Furthermore, specific integration methods utilize Large Language Models to perform Named Entity Recognition and Linking before executing SPARQL queries against databases like DBpedia, as detailed in [3] and [4].

Facts (4)

Sources

Integrating Knowledge Graphs into RAG-Based LLMs to Improve ... thesis.unipd.it Università degli Studi di Padova 2 facts

procedureThe proposed method for integrating knowledge graphs with LLMs utilizes Named Entity Recognition (NER) and Named Entity Linking (NEL) combined with SPARQL queries directed at the DBpedia knowledge graph.

procedureThe proposed method in the thesis integrates knowledge graphs with Large Language Models by combining Named Entity Recognition (NER) and Named Entity Linking (NEL) with SPARQL queries to the DBpedia knowledge graph.

Grounding LLM Reasoning with Knowledge Graphs - arXiv arxiv.org arXiv 1 fact

procedureThere are four primary methods for integrating Knowledge Graphs with Large Language Models: (1) learning graph representations, (2) using Graph Neural Network (GNN) retrievers to extract entities as text input, (3) generating code like SPARQL queries to retrieve information, and (4) using step-by-step interaction methods for iterative reasoning.

LLM-KG4QA: Large Language Models and Knowledge Graphs for ... github.com GitHub 1 fact

referenceThe field of Natural Language to Graph Query Language (NL2GQL) research focuses on translating natural language questions into graph query languages like Cypher or SPARQL, often utilizing Large Language Models to bridge the gap between natural language and structured graph databases.