Logical approaches-and ontologies in particular-offer a well-adapted framework for representing knowledge present on the Semantic Web (
). These ontologies are formulated in
), which are based on expressive
are a subset of
) that provides decidable reasoning. Based on
, it is possible to rely on inference mechanisms to obtain new knowledge from axioms, rules and facts specified in the ontologies. However, these classical inference mechanisms do not deal with :
probabilities. Several works recently targeted those issues (i.e.
, etc.), but none of them combines
) formalism. Several open source software packages for
are available (e.g.
, etc.). In this paper, we present
, a Java framework for reasoning with probabilistic information in the
incorporate three open source software packages for
, which is able to reason with uncertainty information, showing that it can be used in several real-world domains. We also show several experiments of our tool with different ontologies.