Triple
T2462523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford CD6 platform (sixth generation) |
E54563
|
entity |
| Predicate | supportsPowertrain |
P8242
|
FINISHED |
| Object | turbocharged gasoline engines |
—
|
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: turbocharged gasoline engines | Statement: [Ford CD6 platform (sixth generation), supportsPowertrain, turbocharged gasoline engines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsPowertrain Context triple: [Ford CD6 platform (sixth generation), supportsPowertrain, turbocharged gasoline engines]
-
A.
offersPowertrain
chosen
Indicates that one entity provides or makes available a specific powertrain to another entity or for a particular product.
-
B.
powertrainComponentOf
Indicates that one entity is a component or subsystem that forms part of the powertrain of another entity.
-
C.
winnerPowertrainType
Indicates the type of powertrain used by the entity that is identified as the winner in a given context or competition.
-
D.
supportsVehicle
Indicates that one entity provides the necessary strength, stability, or structure to bear the weight of a vehicle.
-
E.
powertrainLocation
Indicates the physical placement or mounting position of a vehicle’s powertrain relative to the rest of the vehicle.
- 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd49c5aa081909ab4f726a458b77f |
completed | March 7, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69abd0b199488190aa381b36593ae1ac |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:44 p.m.