Probabilistic Datalog+/- under the Distribution Semantics

We apply the distribution semantics for probabilistic ontologies (named DISPONTE) to the Datalog+/- language. In DISPONTE the formulas of a probabilistic ontology can be annotated with an epistemic or a statistical probability. The epistemic probability represents a degree of confidence in the formula, while the statistical probability considers the populations to which the formula is applied. The probability of a query is defined in terms of finite set of finite explanations for the query, where an explanation is a set of possibly instantiated formulas that is sufficient for entailing the query. The probability of a query is computed from the set of explanations by making them mutually exclusive. We also compare the DISPONTE approach for Datalog+/- ontologies with that of Probabilistic Datalog+/-, where an ontology is composed of a Datalog+/- theory whose formulas are associated to an assignment of values for the random variables of a companion Markov Logic Network