Triple
T33986540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KITT |
E871426
|
entity |
| Predicate | baseVehicleModelInSeries |
P39689
|
FINISHED |
| Object | 1982 Pontiac Firebird 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 Firebird Trans Am | Statement: [KITT, baseVehicleModelInSeries, 1982 Pontiac Firebird Trans Am]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: baseVehicleModelInSeries Context triple: [KITT, baseVehicleModelInSeries, 1982 Pontiac Firebird Trans Am]
-
A.
hasModelSeries
chosen
Indicates a relationship where an item or product is associated with a specific model series it belongs to.
-
B.
carModel
Indicates the specific model designation of a car within a particular make or brand.
-
C.
vehicleVariant
Indicates that one vehicle is a specific version, model, or configuration variant of another related vehicle.
-
D.
usedVehicleModel
Indicates that a vehicle is a pre-owned (used) instance of a particular vehicle model.
-
E.
resultedInVehicleVariant
Indicates that one event, process, or action led to the creation or emergence of a specific variant of a 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_69f3499e964c8190b674b03f6f791b4b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7064e906881909c3186c646145d34 |
completed | May 3, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69f70100ec1c8190a6b97f50e88891f2 |
completed | May 3, 2026, 8:02 a.m. |
Created at: May 1, 2026, 1:50 a.m.