Triple
T29817202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pacific |
E757142
|
entity |
| Predicate | hasLeadingTruckType |
P122770
|
FINISHED |
| Object | two-axle leading truck |
—
|
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: two-axle leading truck | Statement: [Pacific, hasLeadingTruckType, two-axle leading truck]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLeadingTruckType Context triple: [Pacific, hasLeadingTruckType, two-axle leading truck]
-
A.
hasSeparateLeadingTruck
Indicates that an object or vehicle is accompanied by a distinct, independently operated leading truck unit.
-
B.
hasSeparateTrailingTruck
Indicates that an entity is accompanied by a distinct, independently attached trailing truck or carriage rather than having it integrated into its main structure.
-
C.
hasTruckTraffic
Indicates that there is truck-related vehicular movement or flow occurring on or through a specified location or route.
-
D.
hasTrailerCar
Indicates that one vehicle is connected to and pulling another vehicle configured as a trailer car.
-
E.
hasLeadingWheelArrangement
chosen
Indicates the specific configuration of the leading (front) wheels in a vehicle’s or locomotive’s wheel arrangement.
- 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_69f2245701c88190ad42415a0956c4ed |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fba2877b248190a974eb092243c0c4 |
completed | May 6, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69fb8d06a1b48190a937aa410d159dfa |
completed | May 6, 2026, 6:48 p.m. |
Created at: April 29, 2026, 5:27 p.m.