Recognises a field meaning change with no cut-over date
A field known to have changed meaning, with no date.
Can AI do this?
Not settled yet The benchmark tested this, but the models' answers do not settle yet whether they master it. 0 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 84% | Not shown |
| gemini-3.5-flash-lite | Low cost | 82% | Not shown |
| gpt-6-luna | Low cost | 35% | Not shown |
| claude-haiku-5-5 | Low cost | 82% | Not shown |
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 field, both meanings and the date needed
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: FP-004 LN_RATE "nominal rate; before the 2019 migration held the effective rate" - no date Acceptable: Change recorded with cut-over date 2019-04-01
Also known as: Meaning changed with no cut-over date
Related knobits
Builds on
Usually followed by
All 13 knobits of Analyse and profile the sources.
Source: Review checklist 01-source-analysis, row 2 (DMBOK ch. 8)