Triple
T3467472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southwest monsoon |
E73171
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | monsoon system |
C3904
|
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: monsoon system Context triple: [Southwest monsoon, instanceOf, monsoon system]
-
A.
atmospheric–oceanic oscillation
An atmospheric–oceanic oscillation is a large-scale, recurring pattern of coupled variations in the atmosphere and ocean that influences climate and weather over seasonal to multidecadal timescales.
-
B.
regional wind
A regional wind is a persistent or recurring air movement pattern that is characteristic of and largely confined to a specific geographic area, influenced by local topography, land–sea contrasts, and regional climate conditions.
-
C.
climate phenomenon
chosen
A climate phenomenon is a recurring or notable pattern or event in the Earth’s climate system, such as El Niño or monsoon cycles, that significantly influences weather and environmental conditions over large regions and timescales.
-
D.
component of Global Data-processing and Forecasting System
A component of the Global Data-processing and Forecasting System is a modular subsystem that ingests, processes, analyzes, or disseminates environmental data to support the generation and delivery of global forecasts and related products.
-
E.
component of Global Data-processing and Forecasting System
A component of the Global Data-processing and Forecasting System is a modular subsystem that ingests, transforms, analyzes, or disseminates environmental data to support the generation and delivery of timely, accurate global forecasts.
- F. None of above.
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_69ad85b224d481908ff8be51338d24ff |
completed | March 8, 2026, 2:20 p.m. |
Created at: March 8, 2026, 3:17 p.m.