Recovering Explanations from Transformed Rule-Based Ontologies
Quick summary
arXiv:2608.06399v1 Announce Type: cross Abstract: Datalog rules are often used to define ontologies over Knowledge Graphs. Rule reasoners routinely optimise such ontologies by rewriting their rules into a form that can be evaluated more efficiently. These transformations preserve the entailed facts, but not the structure of the underlying derivations. A proof tree under the rewritten rules explains why a fact holds, but does not readily yield an explanation in terms of the original rules. We study the problem of constructing, from a proof of entailment under the rewritten rules, a proof under
Key takeaways
- arXiv:2608.06399v1 Announce Type: cross Abstract: Datalog rules are often used to define ontologies over Knowledge Graphs.
- Rule reasoners routinely optimise such ontologies by rewriting their rules into a form that can be evaluated more efficiently.
- These transformations preserve the entailed facts, but not the structure of the underlying derivations.
Why it matters
“Recovering Explanations from Transformed Rule-Based Ontologies” highlights the need for repeatable measurement rather than a single impressive demonstration. Independent validation across datasets and clearly stated limitations determine whether a result can guide product decisions.
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