Triple
T33386908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siemens SD-460 |
E854938
|
entity |
| Predicate | numberOfTrucks |
—
|
GENERATED |
| Object | 3 |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTrucks Context triple: [Siemens SD-460, numberOfTrucks, 3]
-
A.
numberOfVehicles
chosen
Indicates the total count of vehicles associated with a given entity or context.
-
B.
numberOfPassengerCars
Indicates the total count of passenger cars associated with or contained in a given entity or context.
-
C.
numberOfTrailerCarsBuilt
Indicates the total count of trailer cars that have been constructed.
-
D.
hasTruckTraffic
Indicates that there is truck-related vehicular movement or flow occurring on or through a specified location or route.
-
E.
numberOfCarsPerUnit
Indicates the quantity of cars associated with each single unit of a specified measure (such as time, distance, or entity).
- F. None of above.
Provenance (1 batch)
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_69f3496d54048190a1cb91fdd7caa6ea |
completed | April 30, 2026, 12:22 p.m. |
Created at: May 1, 2026, 1:35 a.m.