Triple
T5259457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Dark Spot |
E118786
|
entity |
| Predicate | atmosphericCirculation |
P44464
|
FINISHED |
| Object | anticyclonic |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
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.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: anticyclonic | Statement: [Great Dark Spot, atmosphericCirculation, anticyclonic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: atmosphericCirculation Context triple: [Great Dark Spot, atmosphericCirculation, anticyclonic]
-
A.
oceanCirculation
Indicates the movement and flow patterns of seawater within and between oceans, including currents, mixing, and large-scale circulation systems.
-
B.
atmosphericStudyType
Indicates the specific kind or category of study being conducted on the atmosphere or atmospheric phenomena.
-
C.
hasAtmosphericFeature
Indicates that one entity possesses or exhibits a particular feature or characteristic of its atmosphere.
-
D.
dominantWindSystem
chosen
Indicates that one wind pattern or circulation system is the primary or prevailing influence over atmospheric conditions in a given region or period.
-
E.
climateDriver
Indicates a factor or process that significantly influences or drives changes in climate conditions.
- F. None of above.
Provenance (3 batches)
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_69bd446a42c88190b7ecbef006561d55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bcced6881909bdb7ac5471a37fe |
completed | March 20, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69bd77c55224819096c0bcfcfae79bd3 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:50 p.m.