Triple
T37308524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Atlantic jet stream |
E926142
|
entity |
| Predicate | influencesWeatherOf |
P111264
|
FINISHED |
| Object | North America |
—
|
NE NERFINISHED |
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: North America | Statement: [North Atlantic jet stream, influencesWeatherOf, North America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencesWeatherOf Context triple: [North Atlantic jet stream, influencesWeatherOf, North America]
-
A.
hasClimateInfluence
Indicates that one entity affects or contributes to the climate characteristics or climate-related conditions of another entity.
-
B.
hasSignificantWeatherInfluence
chosen
Indicates that one entity exerts a substantial impact on the weather conditions or patterns experienced by another entity or region.
-
C.
snowInfluence
Indicates that one entity affects, alters, or contributes to the presence, behavior, or characteristics of snow in relation to another entity or context.
-
D.
hasExtremeWeatherCharacteristic
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
E.
hasClimate
Indicates that an entity possesses or is characterized by a particular type of climate or climatic 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_69f76eb1bc508190924e9fa5d8acdeb3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd7b0503a08190ba07338365b6fcc9 |
completed | May 8, 2026, 5:56 a.m. |
| PD | Predicate disambiguation | batch_69fd7a9733dc81909199f453c0cc2bc1 |
completed | May 8, 2026, 5:54 a.m. |
Created at: May 3, 2026, 4:16 p.m.