# Goal-Driven Query Answering for Existential Rules with Equality

arXiv: https://arxiv.org/abs/1711.05227 · HTML: https://mlsanity.com/paper/1711.05227/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Nov 2017.

## Built on by (most cited first, 1 of 1)

- [Materializing Knowledge Bases via Trigger Graphs](https://mlsanity.com/paper/2102.02753/) (2021)

## Abstract (arXiv)

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