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

arXiv 2303.07469 ↗First posted 13 Mar 2023cs.DB cs.AI cs.LOcited by 1

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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.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 3 of its 39 references that are in the map. First posted on arXiv 13 Mar 2023.

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3 of 39 references.

References · 3

  1. 2014The DL-Lite Family and Relationscited by 20
  2. 2014Acyclicity Notions for Existential Rules and Their Application to Query Answering in Ontologiescited by 10
  3. 2013Anatomy of the chasecited by 5

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