Triple
T7426497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Bull Air Race World Championship |
E171380
|
entity |
| Predicate | pylonBrandName |
P76923
|
FINISHED |
| Object | Air Gates |
—
|
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: Air Gates | Statement: [Red Bull Air Race World Championship, pylonBrandName, Air Gates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pylonBrandName Context triple: [Red Bull Air Race World Championship, pylonBrandName, Air Gates]
-
A.
pylonType
Indicates the specific structural or functional category that a pylon belongs to within a given context.
-
B.
pylonMaterial
Indicates that a pylon is made of, constructed from, or primarily composed of a specified material.
-
C.
cameraBranding
Indicates that one entity serves as the brand or branding designation associated with a camera or camera product.
-
D.
hasPylon
Indicates that one entity possesses, includes, or is equipped with a pylon as part of its structure or configuration.
-
E.
hasPylonColor
Indicates that an entity (such as a pylon or structure) possesses a specific color as one of its attributes.
- F. None of above. chosen
Provenance (4 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_69c68a63491881909281f73d4d5643bf |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f3055b7881908269ab909c5a85b5 |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f03648d08190b862d07fef71210c |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f1ee5ab8819091082324f2dc3b8c |
completed | March 27, 2026, 9:09 p.m. |
Created at: March 27, 2026, 3:12 p.m.