Triple
T35952245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pontiac dealerships |
E1039760
|
entity |
| Predicate | soldVehicleCategory |
P1776
|
FINISHED |
| Object | passenger cars |
—
|
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: passenger cars | Statement: [Pontiac dealerships, soldVehicleCategory, passenger cars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: soldVehicleCategory Context triple: [Pontiac dealerships, soldVehicleCategory, passenger cars]
-
A.
listedVehicle
Indicates that a vehicle has been placed on a list, such as a registry, catalog, or inventory, as part of a tracking or management process.
-
B.
usedVehicleModel
Indicates that a vehicle is a pre-owned (used) instance of a particular vehicle model.
-
C.
vehicleUsed
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
-
D.
vehicleType
chosen
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
E.
vehicleBase
Indicates that one entity serves as the foundational or underlying base for a vehicle-related entity or system.
- 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_69f76e25ea488190b7cee970b3e70382 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7ac23d1388190bdf9628b294943bd |
completed | May 3, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f7ab734d848190a84f9b8c3a952b75 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.