Recognises two metamodel classes for one thing
Two classes realising the same metadata, populated from the same source.
Can AI do this?
People still lead Few or none of the tested AI models showed they master this. 0 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 80% | Not shown |
| gemini-3.5-flash-lite | Low cost | 8% | Not shown |
| gpt-6-luna | Low cost | 76% | Not shown |
| claude-haiku-5-5 | Low cost | 79% | 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: One class, with the other name as an alias
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: MC-005 Column and MC-012 Field, both from the warehouse schema scan Acceptable: One class, "field" as an alias
Also known as: Two classes for one thing
Related knobits
Builds on
- M-251 Explains metamodel layers, classes and relationships
- M-253 Explains the designation, definition and steward of a registered item
All 12 knobits of Design the metamodel.
Source: Review checklist 02-metamodel, row 1 (11179-3 (one registered item per concept); DMBOK)