Triple
T33986463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knight Rider |
E871424
|
entity |
| Predicate | vehicleModelOfKITT |
P178392
|
FINISHED |
| Object | 1982 Pontiac Trans Am |
—
|
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: 1982 Pontiac Trans Am | Statement: [Knight Rider, vehicleModelOfKITT, 1982 Pontiac Trans Am]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleModelOfKITT Context triple: [Knight Rider, vehicleModelOfKITT, 1982 Pontiac Trans Am]
-
A.
carModel
Indicates the specific model designation of a car within a particular make or brand.
-
B.
vehicleName
Indicates the specific name or designation assigned to a vehicle.
-
C.
racingModel
Indicates that one entity is a specific model or version designed or configured for racing in relation to another entity.
-
D.
hasFictionalVehicle
Indicates that one entity possesses, controls, or is associated with a vehicle that exists only in a fictional or imaginary context.
-
E.
vehicleVariant
Indicates that one vehicle is a specific version, model, or configuration variant of another related vehicle.
- 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_69f3499e964c8190b674b03f6f791b4b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7107acf0481909b01467b9ebbde01 |
completed | May 3, 2026, 9:08 a.m. |
| PD | Predicate disambiguation | batch_69f70f3a54d481909ba6bdda3647b761 |
completed | May 3, 2026, 9:02 a.m. |
| PDg | Predicate description generation | batch_69f70fb41a9c8190a121e62e510dc18a |
completed | May 3, 2026, 9:04 a.m. |
Created at: May 1, 2026, 1:50 a.m.