Explains field semantics and their change over time
A field's meaning, unit and scale are confirmed by its owner; a change of meaning or unit has a cut-over date that mappings split on.
Can AI do this?
AI does this well Most of the tested AI models master this. 4 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 100% | Mastered |
| gemini-3.5-flash-lite | Low cost | 98% | Mastered |
| gpt-6-luna | Low cost | 99% | 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: A field's meaning, unit and scale are confirmed by its owner; a change of meaning or unit has a cut-over date that mappings split on.
How it is assessed: Answers a written question on the field semantics correctly
Related knobits
Needed for
- N-102 Recognises a field meaning change with no cut-over date
- N-107 Recognises a field meaning inferred from its name
- N-131 Dates a meaning change from the value distribution
- N-207 Recognises a mapping ignoring a meaning change
All 13 knobits of Analyse and profile the sources.
Source: Practice the stage 1 reference and review checklist rest on