Explains natural keys, surrogate keys and key stability
What makes a key stable and meaningless, and why a natural key is kept as a unique identifier.
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: What makes a key stable and meaningless, and why a natural key is kept as a unique identifier
How it is assessed: Classifies sample keys as stable or not and meaningful or not, and says which to keep as natural keys
Related knobits
Builds on
Needed for
- K-517 Recognises an unstable or meaningful primary key
- K-518 Recognises an entity identified only by a system-assigned key
- K-610 Recognises a surrogate key without natural-key uniqueness
- K-611 Recognises a surrogate value with meaning, reused or renumbered
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