Enhancing SPARQL Query Rewriting for Complex Ontology Alignments
Abstract
SPARQL query rewriting is a fundamental mechanism for uniformly querying heterogeneous ontologies in the Linked Data Web. However, the complexity of ontology alignments, particularly rich correspondences (c : c), makes this process challenging. Existing approaches primarily focus on simple (s : s) and partially complex ( s : c) alignments, thereby overlooking the challenges posed by more expressive alignments. Moreover, the intricate syntax of SPARQL presents a barrier for non-expert users seeking to fully exploit the knowledge encapsulated in ontologies. This article proposes an innovative approach for the automatic rewriting of SPARQL queries from a source ontology to a target ontology, based on a user's need expressed in natural language. It leverages the principles of equivalence transitivity as well as the advanced capabilities of large language models such as GPT-4. By integrating these elements, this approach stands out for its ability to efficiently handle complex alignments, particularly (c : c) correspondences , by fully exploiting their expressiveness. Additionally, it facilitates access to aligned ontologies for users unfamiliar with SPARQL, providing a flexible solution for querying heterogeneous data.
Cite
@article{arxiv.2505.01309,
title = {Enhancing SPARQL Query Rewriting for Complex Ontology Alignments},
author = {Anicet Lepetit Ondo and Laurence Capus and Mamadou Bousso},
journal= {arXiv preprint arXiv:2505.01309},
year = {2025}
}
Comments
This update corrects a minor error in Table 1 of the originally submitted version, where a formula was inadvertently included. This does not affect the methodology or results. We also improved the formatting of existing formulas and the visual presentation of algorithm outputs. No changes were made to the scientific content