Explains logical relations between rules
Contradiction, redundancy, subsumption and vacuity in a rule set.
Can AI do this?
AI does this well Most of the tested AI models master this. 9 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 | 92% | Not shown |
| 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: Contradiction, redundancy, subsumption and vacuity in a rule set
How it is assessed: Finds the logical relations between sample rules
Related knobits
Builds on
Needed for
- K-301 Recognises contradicting data rules
- K-302 Recognises a data rule no valid data can satisfy
- K-303 Recognises redundant data rules
- K-304 Recognises a data rule implied by another
- K-305 Recognises overlapping value-set rules on one fact type
- K-337 Resolves contradicting rules by adding the missing condition
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