Triple
T21950461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charney–Eliassen model |
E542053
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | atmospheric dynamics model |
C45566
|
CONCEPT FINISHED |
How this triple was built (1 step)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: atmospheric dynamics model Context triple: [Charney–Eliassen model, instanceOf, atmospheric dynamics model]
-
A.
atmospheric general circulation model
An atmospheric general circulation model is a complex numerical model that simulates the three-dimensional, large-scale movement of air and energy in Earth’s atmosphere to study and predict climate and weather patterns.
-
B.
radiative–convective model
A radiative–convective model is a simplified atmospheric model that balances radiative energy transfer with convective heat transport to simulate vertical temperature profiles and climate behavior.
-
C.
numerical weather prediction model
A numerical weather prediction model is a computational system that uses mathematical equations and atmospheric data to simulate and forecast future weather conditions.
-
D.
climate model
A climate model is a computational representation of the Earth’s climate system that simulates interactions among the atmosphere, oceans, land surface, and ice to project past, present, and future climate conditions.
-
E.
atmospheric reanalysis system
An atmospheric reanalysis system is a data assimilation framework that combines historical observations with numerical weather prediction models to produce consistent, gridded reconstructions of past atmospheric states.
- F. None of above. chosen
Provenance (1 batch)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
Created at: April 16, 2026, 7:58 p.m.