A Benchmark for Gap and Overlap Analysis as a Test of KG Task Readiness
Task-oriented evaluation of knowledge graph (KG) quality increasingly asks whether an ontology-based representation can answer the competency questions that users actually care about, in a manner that is reproducible, explainable, and traceable to evidence. This paper adopts that perspective and focuses on gap and overlap analysis for policy-like documents (e.g., insurance contracts), where given a scenario, which documents support it (overlap) and which do not (gap), with defensible justifications. The resulting gap/overlap determinations are typically driven by genuine differences in coverage and restrictions rather than missing data, making the task a direct test of KG task readiness r...
| Authors | Maruf Ahmed Mridul, Rohit Kapa, Oshani Seneviratne |
|---|---|
| Primary category | cs.AI |
| Published | 12 April 2026 |
| Last updated at source | 12 April 2026 |
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