Explains the DCAT 3 catalogue vocabulary
A catalogue of datasets, each with its distributions and the data services serving it, catalogue records, a description and a contact point (W3C DCAT Version 3, 2024).
Can AI do this?
AI does this partly Some of the tested AI models master this; others do not show it. 2 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 98% | Mastered |
| gemini-3.5-flash-lite | Low cost | 38% | Not shown |
| gpt-6-luna | Low cost | 38% | Not shown |
| claude-haiku-5-5 | Low cost | 98% | 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 catalogue of datasets, each with its distributions and the data services serving it, catalogue records, a description and a contact point (W3C DCAT Version 3, 2024).
How it is assessed: Answers a written question on the DCAT catalogue correctly
Related knobits
Needed for
All 12 knobits of Design the metamodel.
Source: Practice the stage 2 reference and review checklist rest on