Recognises a definition carrying non-defining content
The definition carries explanations, examples, process or system details that are not needed to delimit the concept. Move them to a note.
Can AI do this?
People still lead Few or none of the tested AI models showed they master this. 1 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 90% | Mastered |
| gemini-3.1-pro-preview* | Flagship | 0% | Not mastered |
| gpt-6-astra* | Flagship | 100% | Mastered |
| claude-fable-5-1* | Flagship | 100% | Mastered |
| gemini-3.8-flash* | Mid tier | 9% | Not mastered |
| gpt-6.1-sol* | Mid tier | 100% | Mastered |
| claude-sonnet-5-5* | Mid tier | 100% | Mastered |
| gemini-3.5-flash-lite | Low cost | 10% | Not mastered |
| gpt-6-luna | Low cost | 90% | Not shown |
| claude-haiku-5-5 | Low cost | 10% | Not mastered |
* 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 content to move to a note
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: personal loan: unsecured credit granted to a natural person for a fixed term and repaid in instalments; keyed into the core banking system by the branch and needing credit-committee approval above 50 000 EUR Acceptable: personal loan: unsecured credit granted to a natural person for a fixed term and repaid in instalments (core-system and approval details go in a note)
Also known as: Not concise (business term)
Related knobits
Builds on
All 27 knobits of Define business terms in the glossary.
Source: Review checklist 03-business-glossary (metadata-management), row 11; formerly data-modelling K-211