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Inspired by the magic sets for Datalog, we present a novel goal-drivenapproach for answering queries over terminating existential rules with equality(aka TGDs and EGDs). Our technique improves the performance of query answeringby pruning the consequences that are not relevant for the query. This ischallenging in our setting because equalities can potentially affect allpredicates in a dataset. We address this problem by combining the existingsingularization technique with two new ingredients: an algorithm foridentifying the rules relevant to a query and a new magic sets algorithm. Weshow empirically that our technique can significantly improve the performanceof query answering, and that it can mean the difference between answering aquery in a few seconds or not being able to process the query at all.

Goal-Driven Query Answering for Existential Rules with Equality