Triple
T38117780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oldsmobile Toronado |
E951837
|
entity |
| Predicate | firstModelYearEngineDisplacement |
—
|
GENERATED |
| Object | 425 cu in V8 |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstModelYearEngineDisplacement Context triple: [Oldsmobile Toronado, firstModelYearEngineDisplacement, 425 cu in V8]
-
A.
availableEngineDisplacement
Indicates the range or specific values of engine displacement that are offered or applicable for a given entity.
-
B.
engineDisplacement
chosen
Indicates the total volume swept by all the pistons inside an engine’s cylinders during one complete cycle.
-
C.
hasEngineDisplacementClass
Indicates a relationship where a vehicle or engine is assigned to a category based on the size or volume of its engine displacement.
-
D.
originalEngineModel
Indicates that one engine is the original or initial model from which another engine or engine variant is derived.
-
E.
firstModelIntroduced
Indicates that one entity is the earliest or original model introduced in relation to another entity or context.
- F. None of above.
Provenance (1 batch)
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_69f76f07734c8190814e937e12257a78 |
completed | May 3, 2026, 3:51 p.m. |
Created at: May 3, 2026, 4:21 p.m.