Chatbot-Based Ontology Interaction Using Large Language Models and Domain-Specific Standards
This addresses the challenge of querying ontologies for users in domains like knowledge management, though it appears incremental by integrating existing methods with domain-specific standards.
The paper tackled the problem of generating accurate SPARQL queries for ontologies using LLMs and a chatbot interface, resulting in enhanced intuitive access to formalized knowledge with prevention of misinformation.
The following contribution introduces a concept that employs Large Language Models (LLMs) and a chatbot interface to enhance SPARQL query generation for ontologies, thereby facilitating intuitive access to formalized knowledge. Utilizing natural language inputs, the system converts user inquiries into accurate SPARQL queries that strictly query the factual content of the ontology, effectively preventing misinformation or fabrication by the LLM. To enhance the quality and precision of outcomes, additional textual information from established domain-specific standards is integrated into the ontology for precise descriptions of its concepts and relationships. An experimental study assesses the accuracy of generated SPARQL queries, revealing significant benefits of using LLMs for querying ontologies and highlighting areas for future research.