Explains third normal form
No non-prime attribute depends transitively on a candidate key.
Can AI do this?
AI does this well Most of the tested AI models master this. 10 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 | 100% | Mastered |
| 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: No non-prime attribute depends transitively on a candidate key
How it is assessed: Classifies sample entities as in or not in 3NF and names the transitive dependency
Related knobits
Builds on
Needed for
- K-509 Recognises a transitive dependency between non-key attributes
- K-557 Explains Boyce-Codd normal form
- K-651 Explains controlled denormalisation
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