# A Framework for Combining Entity Resolution and Query Answering in Knowledge Bases

arXiv: https://arxiv.org/abs/2303.07469 · HTML: https://mlsanity.com/paper/2303.07469/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 39 references that are in the map.
- First posted on arXiv 13 Mar 2023.

## Builds on (most cited first, 3 of 3)

- [The DL-Lite Family and Relations](https://mlsanity.com/paper/1401.3487/) (2014)
- [Acyclicity Notions for Existential Rules and Their Application to Query Answering in Ontologies](https://mlsanity.com/paper/1406.4110/) (2014)
- [Anatomy of the chase](https://mlsanity.com/paper/1303.6682/) (2013)

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

- [Advances in Logic-Based Entity Resolution: Enhancing ASPEN with Local Merges and Optimality Criteria](https://mlsanity.com/paper/2508.10504/) (2025)

## Abstract (arXiv)

We propose a new framework for combining entity resolution and query answering in knowledge bases (KBs) with tuple-generating dependencies (tgds) and equality-generating dependencies (egds) as rules. We define the semantics of the KB in terms of special instances that involve equivalence classes of entities and sets of values. Intuitively, the former collect all entities denoting the same real-world object, while the latter collect all alternative values for an attribute. This approach allows us to both resolve entities and bypass possible inconsistencies in the data. We then design a chase procedure that is tailored to this new framework and has the feature that it never fails; moreover, when the chase procedure terminates, it produces a universal solution, which in turn can be used to obtain the certain answers to conjunctive queries. We finally discuss challenges arising when the chase does not terminate.