Triple
T26389717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Bull Powertrains (Honda-based) |
E663377
|
entity |
| Predicate | chassisIntegrationWith |
P160485
|
FINISHED |
| Object | Red Bull Racing RB-series cars |
—
|
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 RB-series cars | Statement: [Red Bull Powertrains (Honda-based), chassisIntegrationWith, Red Bull Racing RB-series cars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chassisIntegrationWith Context triple: [Red Bull Powertrains (Honda-based), chassisIntegrationWith, Red Bull Racing RB-series cars]
-
A.
chassis
Indicates that one entity serves as the structural frame or supporting base (chassis) for another entity.
-
B.
chassisFeature
Indicates that a particular feature, component, or characteristic is part of or associated with a chassis.
-
C.
chassisCode
Indicates the specific chassis designation or code assigned to a vehicle model to distinguish its underlying structural platform or variant.
-
D.
supportsChassisType
Indicates that one entity is compatible with and can be used to support or accommodate a specified chassis type.
-
E.
chassisConstruction
Indicates how the chassis of an object is built or assembled, specifying the construction method or structural design used.
- 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_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. |
| PDg | Predicate description generation | batch_69f6018ceb1c8190a6a5f84071659a96 |
completed | May 2, 2026, 1:52 p.m. |
Created at: April 26, 2026, 11:24 p.m.