Triple
T17754348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transit America |
E443193
|
entity |
| Predicate | vehiclePowerCollection |
P128224
|
FINISHED |
| Object | third rail |
—
|
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: third rail | Statement: [Transit America, vehiclePowerCollection, third rail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehiclePowerCollection Context triple: [Transit America, vehiclePowerCollection, third rail]
-
A.
vehiclePower
Indicates the amount or type of power a vehicle can produce or is rated to deliver.
-
B.
enginePower
Indicates the power output produced by an engine, typically quantifying its capability to perform work or generate mechanical energy.
-
C.
winnerPowertrainType
Indicates the type of powertrain used by the entity that is identified as the winner in a given context or competition.
-
D.
powerRange
Indicates the range of power values within which an entity operates, applies, or is considered valid.
-
E.
powerToWeightRatio
Indicates the relationship between an entity’s available power and its mass, expressing how much power is provided per unit of weight.
- F. None of above. chosen
Provenance (4 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4841da9988190b5efde3bbd3f24c3 |
completed | April 19, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69e3cde9dc288190af0e2198487f2051 |
completed | April 18, 2026, 6:31 p.m. |
| PDg | Predicate description generation | batch_69e3cfab7edc8190b663282d565a0389 |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 10:10 a.m.