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Can You Tell the Difference? Contrastive Explanations for ABox Entailments

Published: November 14, 2025 | arXiv ID: 2511.11281v1

By: Patrick Koopmann , Yasir Mahmood , Axel-Cyrille Ngonga Ngomo and more

Potential Business Impact:

Shows why something is true, but another isn't.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

We introduce the notion of contrastive ABox explanations to answer questions of the type "Why is a an instance of C, but b is not?". While there are various approaches for explaining positive entailments (why is C(a) entailed by the knowledge base) as well as missing entailments (why is C(b) not entailed) in isolation, contrastive explanations consider both at the same time, which allows them to focus on the relevant commonalities and differences between a and b. We develop an appropriate notion of contrastive explanations for the special case of ABox reasoning with description logic ontologies, and analyze the computational complexity for different variants under different optimality criteria, considering lightweight as well as more expressive description logics. We implemented a first method for computing one variant of contrastive explanations, and evaluated it on generated problems for realistic knowledge bases.

Country of Origin
🇩🇪 🇳🇱 Germany, Netherlands

Page Count
37 pages

Category
Computer Science:
Artificial Intelligence