# Why not? Developing ABox Abduction beyond Repairs

arXiv: https://arxiv.org/abs/2507.21955 · HTML: https://mlsanity.com/paper/2507.21955/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Jul 2025.

## Built on by (most cited first, 2 of 2)

- [Rethinking Explanations: Formalizing Contrast in Description Logics](https://mlsanity.com/paper/2605.01442/) (2026)
- [NeurOWL: An LLM-Based Neural-symbolic Framework for Incomplete OWL Ontology Reasoning](https://mlsanity.com/paper/2607.15776/) (2026)

## Abstract (arXiv)

Abduction is the task of computing a sufficient extension of a knowledge base (KB) that entails a conclusion not entailed by the original KB. It serves to compute explanations, or hypotheses, for such missing entailments. While this task has been intensively investigated for perfect data and under classical semantics, less is known about abduction when erroneous data results in inconsistent KBs. In this paper we define a suitable notion of abduction under repair semantics, and propose a set of minimality criteria that guides abduction towards `useful' hypotheses. We provide initial complexity results on deciding existence of and verifying abductive solutions with these criteria, under different repair semantics and for the description logics DL-Lite and EL_bot.