Explains Witt's classification of business rules
Data rules (constraints, derivations, data-update rules) versus activity and party rules.
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: Data rules (constraints, derivations, data-update rules) versus activity and party rules
How it is assessed: Classifies sample rules and says which belong in the data model
Related knobits
Needed for
- K-103 Recognises a statement outside the scope of data requirements
- K-113 Recognises a business rule left inside another statement
- K-314 Recognises a data-update rule with no enforcing or detecting mechanism
- K-315 Recognises an activity or party rule claimed as a data rule
All 28 knobits of Document data rules as SBVR fact types and rule statements.
Source: Data-management practice used by the stage 3 reference and review checklist