Triple
T315633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GMT K2XX |
E7699
|
entity |
| Predicate | vehicleClassSupported |
P1776
|
FINISHED |
| Object | full-size pickup truck |
—
|
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: full-size pickup truck | Statement: [GMT K2XX, vehicleClassSupported, full-size pickup truck]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleClassSupported Context triple: [GMT K2XX, vehicleClassSupported, full-size pickup truck]
-
A.
vehicleType
chosen
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
B.
hasVehicle
Indicates that one entity possesses, owns, or is assigned a vehicle.
-
C.
starVehicleFor
Indicates that one entity serves as the primary or featured vehicle associated with another entity, such as a person, production, or event.
-
D.
transportCharacteristic
Indicates a relationship where a specific characteristic, property, or feature is attributed to a mode or instance of transport.
-
E.
transportType
Indicates the mode or means of transportation used in carrying something or someone from one place to another.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea6462148190825acc57f6d2adaf |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e943f12c8190883854aeed974260 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.