Explains metamodel layers, classes and relationships
A metamodel is a model of metadata: classes, attributes and relationships one level above the models they describe (OMG MOF layering of data, model, metamodel and meta-metamodel), its classes in the business, technical or operational layer (DMBOK2 ch. 12 §2.3.1).
Can AI do this?
AI does this well Most of the tested AI models master this. 3 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 100% | Mastered |
| gemini-3.5-flash-lite | Low cost | 30% | Not shown |
| gpt-6-luna | Low cost | 99% | Mastered |
| claude-haiku-5-5 | Low cost | 100% | Mastered |
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: A metamodel is a model of metadata: classes, attributes and relationships one level above the models they describe (OMG MOF layering of data, model, metamodel and meta-metamodel), its classes in the business, technical or operational layer (DMBOK2 ch. 12 §2.3.1).
How it is assessed: Answers a written question on the metamodel correctly
Related knobits
Builds on
Needed for
- M-201 Recognises two metamodel classes for one thing
- M-256 Explains how a metamodel is populated from metadata sources
All 12 knobits of Design the metamodel.
Source: Practice the stage 2 reference and review checklist rest on