reason

Abductive reasoning generates and ranks plausible explanations for observations in a knowledge graph. It formulates hypotheses to diagnose data gaps and infer missing links based on available evidence.

Yes, you can evaluate Datalog and SPARQL programs against your knowledge graph. This query-based reasoning processes structured rules to derive facts and validate logical relationships across the graph data.

Abductive reasoning generates and ranks plausible explanations for observations in a knowledge graph. It produces ranked hypotheses to help diagnose data gaps and infer missing links based on available evidence.

Explainable reasoning provides clear justifications and provenance for all conclusions derived from a knowledge graph. It ensures every deductive or abductive inference is auditable by tracking the formal rules applied.

Rete-based reasoning efficiently processes rules through a forward-chaining engine, suitable for complex pattern matching. Standard deductive queries derive specific conclusions from known facts using formal logical rules applied directly to the graph.