Derives the broader concept from the head of a definition
Builds a taxonomy from definitions by reading each definition's superordinate concept.
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: Kind-of links taken from the head of each definition, with the quoted basis
How it is assessed: Each broader concept is the head of the definition, resolved through listed synonyms, never taken from the term's name or other terms it mentions
Related knobits
Builds on
- K-251 Explains intensional definition by superordinate concept and delimiting characteristics
- K-451 Explains hierarchical relations and the all-and-some test
All 31 knobits of Build the conceptual model and taxonomies.
Source: Graded on its own by the stage 4 skill-tests task; no review-checklist row names it