Triple
T5949844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atchison, Topeka and Santa Fe Railway |
E132368
|
entity |
| Predicate | hadMotivePowerType |
P14429
|
FINISHED |
| Object | steam locomotives |
—
|
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: steam locomotives | Statement: [Atchison, Topeka and Santa Fe Railway, hadMotivePowerType, steam locomotives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadMotivePowerType Context triple: [Atchison, Topeka and Santa Fe Railway, hadMotivePowerType, steam locomotives]
-
A.
hasMotivePowerType
chosen
Indicates that an entity (such as a vehicle or machine) operates using a specified type of motive power (e.g., electric, diesel, steam).
-
B.
vehiclePower
Indicates the amount or type of power a vehicle can produce or is rated to deliver.
-
C.
electricMotorType
Indicates the specific kind or category of electric motor associated with an entity.
-
D.
winnerPowertrainType
Indicates the type of powertrain used by the entity that is identified as the winner in a given context or competition.
-
E.
enginePower
Indicates the power output produced by an engine, typically quantifying its capability to perform work or generate mechanical energy.
- 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_69c00869d3308190af89b2453e0f7546 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0335806788190b6488ca8b73f7a63 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4:02 p.m.