AAAI 2025technical0 citations

Consistent Query Answering over Existential Rules with Open and Closed Predicates

Lorenzo Marconi, Riccardo Rosati

Abstract

We study Consistent Query Answering (CQA) over knowledge bases with existential rules. Specifically, we propose a novel framework for CQA that combines previous approaches, allowing for the simultaneous presence of both open and closed predicates, i.e. predicates interpreted under open- and closed-world assumption, respectively. We establish the data complexity of answering unions of conjunctive queries in such a new framework under the so-called AR semantics and for different classes of existential rules. We also provide new complexity results for the standard (i.e. non-inconsistency tolerant) query answering in the presence of both open and closed predicates. Our results show that, for certain classes of rules, the complexity of CQA matches that of non-inconsistency-tolerant query answering.

BibTeX
@article{Marconi_Rosati_2025, title={Consistent Query Answering over Existential Rules with Open and Closed Predicates}, volume={39}, url={https://ojs.aaai.org/index.php/AAAI/article/view/33654}, DOI={10.1609/aaai.v39i14.33654}, abstractNote={We study Consistent Query Answering (CQA) over knowledge bases with existential rules. Specifically, we propose a novel framework for CQA that combines previous approaches, allowing for the simultaneous presence of both open and closed predicates, i.e. predicates interpreted under open- and closed-world assumption, respectively. We establish the data complexity of answering unions of conjunctive queries in such a new framework under the so-called AR semantics and for different classes of existential rules. We also provide new complexity results for the standard (i.e. non-inconsistency tolerant) query answering in the presence of both open and closed predicates. Our results show that, for certain classes of rules, the complexity of CQA matches that of non-inconsistency-tolerant query answering.}, number={14}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Marconi, Lorenzo and Rosati, Riccardo}, year={2025}, month={Apr.}, pages={15083-15091} }