Triple
T35752390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 Spanish Grand Prix |
E1033350
|
entity |
| Predicate | constructorOfWinningCar |
P183252
|
FINISHED |
| Object | Red Bull Racing-TAG Heuer |
—
|
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-TAG Heuer | Statement: [2016 Spanish Grand Prix, constructorOfWinningCar, Red Bull Racing-TAG Heuer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: constructorOfWinningCar Context triple: [2016 Spanish Grand Prix, constructorOfWinningCar, Red Bull Racing-TAG Heuer]
-
A.
manufacturerOfWinningCar
chosen
Indicates that an entity is the manufacturer responsible for producing the car that won a particular race or competition.
-
B.
winningCar
Indicates that a particular car is the one that has achieved first place or victory in a race or competition.
-
C.
engineManufacturerOfWinningCar
Indicates that an entity is the manufacturer of the engine used in the car that won a particular race or competition.
-
D.
chassisManufacturerOfWinningCar
Indicates that a manufacturer built the chassis of the car that won a particular race or competition.
-
E.
championshipWinningCar
Indicates that a car is the specific vehicle that won a particular championship.
- 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_69f76e1262f48190a313318665acc189 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd974d75e08190af46b1d608769f3b |
completed | May 8, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69fd94ff792c8190bedf4a639d3da809 |
completed | May 8, 2026, 7:47 a.m. |
Created at: May 3, 2026, 4:06 p.m.