  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.
