# Repairing Ontologies via Axiom Weakening

arXiv: https://arxiv.org/abs/1711.03430 · HTML: https://mlsanity.com/paper/1711.03430/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Nov 2017.

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

- [Repairing EL Ontologies Using Weakening and Completing](https://mlsanity.com/paper/2208.00486/) (2022)
- [FALCON: Scalable Reasoning over Inconsistent ALC Ontologies](https://mlsanity.com/paper/2208.07628/) (2022)
- [Repairing Networks of EL_perp Ontologies using Weakening and Completing -- Extended version](https://mlsanity.com/paper/2407.18848/) (2024)
- [Consistency Is Not Coherence: Orientation Search for Certified Alignments Between 4D Defence Upper Ontologies](https://mlsanity.com/paper/2608.21914/) (2026)
- [Ontology-Grounded, Reasoner-Verified Benchmarks for Evaluating LLM Reasoning in Scientific AI](https://mlsanity.com/paper/2610.00682/) (2026)

## Abstract (arXiv)

Ontology engineering is a hard and error-prone task, in which small changes may lead to errors, or even produce an inconsistent ontology. As ontologies grow in size, the need for automated methods for repairing inconsistencies while preserving as much of the original knowledge as possible increases. Most previous approaches to this task are based on removing a few axioms from the ontology to regain consistency. We propose a new method based on weakening these axioms to make them less restrictive, employing the use of refinement operators. We introduce the theoretical framework for weakening DL ontologies, propose algorithms to repair ontologies based on the framework, and provide an analysis of the computational complexity. Through an empirical analysis made over real-life ontologies, we show that our approach preserves significantly more of the original knowledge of the ontology than removing axioms.