Recognises a check on the wrong object
The check reads a table or column other than the one its rule constrains. Common where requirement tables put a rule in the row next to the one it belongs to, and the check was written from the row.
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 | 72% | Not shown |
| gemini-3.1-pro-preview* | Flagship | 45% | Not shown |
| gpt-6-astra* | Flagship | 100% | Mastered |
| claude-fable-5-1* | Flagship | 100% | Mastered |
| gemini-3.8-flash* | Mid tier | 75% | Not shown |
| gpt-6.1-sol* | Mid tier | 99% | Mastered |
| claude-sonnet-5-5* | Mid tier | 99% | Mastered |
| gemini-3.5-flash-lite | Low cost | 70% | Not shown |
| gpt-6-luna | Low cost | 75% | Not shown |
| claude-haiku-5-5 | Low cost | 73% | Not shown |
* From the earlier benchmark of 2026-10: 10 data-modelling test tasks, 3 runs per task, graded by claude-opus-5-5. These models have not taken the current 123 tasks yet; the two methods differ, so compare their figures with care. They are left out of the “most models” counts and the best-model picks.
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: The check and the column its rule constrains
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: BR-012 constrains makse väärtuspäev (LA-018); DQ-015 cites BR-012 and checks kontojaak Acceptable: DQ-015.columns is the column implementing LA-018, and the expression reads it (DQR-024, DQR-005)
Also known as: Check on the wrong object (data quality rule)
Related knobits
Builds on
All 30 knobits of Derive data quality rules.
Source: Review checklist 03-dq-rules (data-quality), row 10; this skill; Olson 2003; formerly data-modelling K-710