Triple
T26389962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Visa Cash App RB Formula One Team |
E663382
|
entity |
| Predicate | windTunnelPartner |
P82786
|
FINISHED |
| Object | Red Bull Racing |
—
|
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: Red Bull Racing | Statement: [Visa Cash App RB Formula One Team, windTunnelPartner, Red Bull Racing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: windTunnelPartner Context triple: [Visa Cash App RB Formula One Team, windTunnelPartner, Red Bull Racing]
-
A.
usesWindTunnelOf
chosen
Indicates that one entity makes use of another entity’s wind tunnel facility for testing, experimentation, or related aerodynamic activities.
-
B.
conductedWindTunnelTests
Indicates that wind tunnel experiments or evaluations were performed on an object, design, or system.
-
C.
aircraftManufacturerPartner
Indicates a partnership relationship between an aircraft manufacturer and another entity, typically for collaboration in design, production, or related aerospace activities.
-
D.
airWingType
Indicates the classification or category of an air wing associated with an entity.
-
E.
windResistance
Indicates the degree to which an entity opposes or reduces the effect of wind acting upon it.
- 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_69ee88374adc81909868f3bab374a32f |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f610be3e848190b7acb7675e37e1f5 |
completed | May 2, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f5f800fa9c8190aab0962669fde8ac |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 26, 2026, 11:25 p.m.