# Connection-minimal Abduction in EL via Translation to FOL -- Technical Report

arXiv: https://arxiv.org/abs/2205.08449 · HTML: https://mlsanity.com/paper/2205.08449/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 45 references that are in the map.
- First posted on arXiv 17 May 2022.

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

- [Signature-Based Abduction for Expressive Description Logics -- Technical Report](https://mlsanity.com/paper/2007.00757/) (2020)
- [Reasoning about Explanations for Negative Query Answers in DL-Lite](https://mlsanity.com/paper/1402.0575/) (2014)
- [A Generic Framework for Implicate Generation Modulo Theories](https://mlsanity.com/paper/1807.04557/) (2018)

## Built on by (most cited first, 5 of 5)

- [Can You Tell the Difference? Contrastive Explanations for ABox Entailments](https://mlsanity.com/paper/2511.11281/) (2025)
- [ABox Abduction for Inconsistent Knowledge Bases under Repair Semantics](https://mlsanity.com/paper/2605.01341/) (2026)
- [Why Not? Explaining Missing Entailments with Evee (Technical Report)](https://mlsanity.com/paper/2308.07294/) (2023)
- [Repairing Networks of EL_perp Ontologies using Weakening and Completing -- Extended version](https://mlsanity.com/paper/2407.18848/) (2024)
- [NeurOWL: An LLM-Based Neural-symbolic Framework for Incomplete OWL Ontology Reasoning](https://mlsanity.com/paper/2607.15776/) (2026)

## Abstract (arXiv)

Abduction in description logics finds extensions of a knowledge base to make it entail an observation. As such, it can be used to explain why the observation does not follow, to repair incomplete knowledge bases, and to provide possible explanations for unexpected observations. We consider TBox abduction in the lightweight description logic EL, where the observation is a concept inclusion and the background knowledge is a TBox, i.e., a set of concept inclusions. To avoid useless answers, such problems usually come with further restrictions on the solution space and/or minimality criteria that help sort the chaff from the grain. We argue that existing minimality notions are insufficient, and introduce connection minimality. This criterion follows Occam's razor by rejecting hypotheses that use concept inclusions unrelated to the problem at hand. We show how to compute a special class of connection-minimal hypotheses in a sound and complete way. Our technique is based on a translation to first-order logic, and constructs hypotheses based on prime implicates. We evaluate a prototype implementation of our approach on ontologies from the medical domain.