Triple
T1377153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Presidency of the United States |
E29250
|
entity |
| Predicate | officialVehicle |
P7735
|
FINISHED |
| Object | presidential state car of the United States |
—
|
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: presidential state car of the United States | Statement: [Presidency of the United States, officialVehicle, presidential state car of the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officialVehicle Context triple: [Presidency of the United States, officialVehicle, presidential state car of the United States]
-
A.
vehicleUsed
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
-
B.
hasVehicle
chosen
Indicates that one entity possesses, owns, or is assigned a vehicle.
-
C.
vehicleType
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
D.
starVehicleFor
Indicates that one entity serves as the primary or featured vehicle associated with another entity, such as a person, production, or event.
-
E.
intendedCrewVehicle
Indicates that a particular vehicle is designated or planned to be used by a specific crew.
- 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c31602b8819087a57e8d390cae7a |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4befcabdc8190a9f05d002603f81c |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.