Explains supertype and subtype constraints
Disjoint or overlapping, total or partial subtyping, and what each allows.
Can AI do this?
AI does this well Most of the tested AI models master this. 9 of 10 models master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 100% | Mastered |
| gemini-3.1-pro-preview | Flagship | 100% | Mastered |
| gpt-6-astra | Flagship | 100% | Mastered |
| claude-fable-5-1 | Flagship | 100% | Mastered |
| gemini-3.8-flash | Mid tier | 100% | Mastered |
| gpt-6.1-sol | Mid tier | 100% | Mastered |
| claude-sonnet-5-5 | Mid tier | 100% | Mastered |
| gemini-3.5-flash-lite | Low cost | 89% | Not shown |
| gpt-6-luna | Low cost | 100% | 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: Disjoint or overlapping, total or partial subtyping, and what each allows
How it is assessed: States the disjointness and completeness of sample subtypings from their business rules
Related knobits
Needed for
- K-516 Recognises attributes inapplicable to some instances
- K-519 Recognises undeclared subtype constraints
- K-536 Introduces subtypes for attributes applying to only some instances
- K-652 Explains the implementation options for subtypes
All 56 knobits of Derive the logical data model.
Source: Normalisation theory and relational design (Codd, Fagin, Date), as used by the stage 5 reference and review checklist