Logic programming techniques for reasoning with probabilistic ontologies

The increasing popularity of the Semantic Web drove to a widespread adoption of Description Logics (DLs) for modeling real world domains. To help the diffusion of DLs, a large number of reasoning algorithms have been developed. Usually these algorithms are implemented in procedural languages such as Java or C++. Most of the reasoners exploit the tableau algorithm which has to manage non-determinism, a feature that is not easy to handle using such languages. Reasoning on real world domains also requires the capability of managing probabilistic and uncertain information. We thus present TRILL, for “Tableau Reasoner for descrIption Logics in proLog”, that implements a tableau algorithm and is able to return explanations for queries and their corresponding probability, and TRILLP , for “TRILL powered by Pinpointing formulas”, which is able to compute a Boolean formula representing the set of explanations for a query. This approach can speed up the process of computing the probability. Prolog non-determinism allows us to easily handle the tableau’s non-deterministic expansion rules.