Recognises an entity in two subject areas
One entity placed twice: two owners for one concept.
Can AI do this?
Not settled yet The benchmark tested this, but the models' answers do not settle yet whether they master it. 0 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 56% | Not shown |
| gemini-3.5-flash-lite | Low cost | 52% | Not shown |
| gpt-6-luna | Low cost | 56% | Not shown |
| claude-haiku-5-5 | Low cost | 55% | Not shown |
Mastered means a probability of at least 90% that the model has this knobit, estimated from its graded answers. “Not shown” means the answers do not settle it either way. How the models are tested.
What it looks like in practice
Expected result: The entity and its one subject area
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: EN-003 Account Holder in SA-001 and SA-003 Acceptable: One subject area (Party, as a role), consulted by the other
Also known as: Entity in two subject areas
Related knobits
Builds on
All 17 knobits of Build the enterprise data model of subject areas.
Source: Review checklist 02-enterprise-data-model, row 2 (DMBOK)