Maps an application model onto a canonical model
Each application attribute mapped to a canonical attribute, with gaps and transformations stated
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 | 89% | Not shown |
| gemini-3.5-flash-lite | Low cost | 89% | Not shown |
| gpt-6-luna | Low cost | 89% | Not shown |
| claude-haiku-5-5 | Low cost | 89% | 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: Each application attribute mapped to a canonical attribute, with gaps and transformations stated
How it is assessed: A card system's customer record mapped onto the bank's canonical party model: every field mapped or stated as a gap, code values translated, and nothing invented in the canonical model for one application
Related knobits
Builds on
All 59 knobits of Derive the logical data model.
Source: DAMA-DMBOK2 chapter 5, element(s) DM-18: a performance at CDMP Practitioner level