Triple
T17069344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union Pacific Heritage Fleet |
E414171
|
entity |
| Predicate | heritageCarType |
P47469
|
FINISHED |
| Object | dome car |
—
|
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: dome car | Statement: [Union Pacific Heritage Fleet, heritageCarType, dome car]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heritageCarType Context triple: [Union Pacific Heritage Fleet, heritageCarType, dome car]
-
A.
historicRacingCar
Indicates that an entity is a racing car of historical significance, typically from a past era of motorsport competition.
-
B.
carriageType
chosen
Indicates the specific kind or category of carriage associated with or used in relation to an entity.
-
C.
vehicleType
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
D.
notableCar
Indicates that the subject is a car recognized for its significance, prominence, or special interest (e.g., historically, culturally, or technically).
-
E.
championshipWinningCar
Indicates that a car is the specific vehicle that won a particular championship.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbbfb1f08190807301ff6e573cf5 |
completed | April 18, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69e35d642f74819098c014135e249b27 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:34 a.m.