Triple
T6955470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Köppen Am |
E161231
|
entity |
| Predicate | hasAssociatedWeatherSystem |
P32056
|
FINISHED |
| Object | monsoon circulation |
—
|
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: monsoon circulation | Statement: [Köppen Am, hasAssociatedWeatherSystem, monsoon circulation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedWeatherSystem Context triple: [Köppen Am, hasAssociatedWeatherSystem, monsoon circulation]
-
A.
associatedWithWeather
chosen
Indicates a relationship where something is connected or related to weather conditions or phenomena.
-
B.
hasMeteorologicalStation
Indicates that one entity possesses, hosts, or is equipped with a meteorological station used for observing and recording weather-related data.
-
C.
hasClimateSystem
Indicates that one entity possesses or is characterized by a particular climate system.
-
D.
associatedWithPrecipitationType
Indicates that there is a relationship between an entity and a specific type or category of precipitation (such as rain, snow, or hail).
-
E.
isTropicalCycloneBasin
Indicates that a given geographic region or body of water functions as a basin where tropical cyclones can form or occur.
- 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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dacf8c8c8190a25dbacebeb4b66e |
completed | March 27, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bf0a7c8190b5ed4aca22ba9b97 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:29 p.m.