Recognises overlapping subject areas
Two subject areas whose definitions cover the same things; entities will be placed by whoever models first.
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 | 74% | Not shown |
| gemini-3.5-flash-lite | Low cost | 38% | Not shown |
| gpt-6-luna | Low cost | 74% | Not shown |
| claude-haiku-5-5 | Low cost | 76% | 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 pair and the discriminating definition or merge
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: SA-001 Party and SA-002 Customer ("persons who hold a product") Acceptable: Customer is a role of a Party, an entity in SA-001; SA-002 retired
Also known as: Overlapping subject areas
Related knobits
Builds on
- A-251 Explains the enterprise data model and its subject areas
- A-254 Explains definitions distinguishing a concept
All 17 knobits of Build the enterprise data model of subject areas.
Source: Review checklist 02-enterprise-data-model, row 1 (DMBOK; 704)