Triple
T25464707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Truck and Bus Regulation |
E638141
|
entity |
| Predicate | targetedVehicleClass |
P97747
|
FINISHED |
| Object | Class 7 trucks |
—
|
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: Class 7 trucks | Statement: [Truck and Bus Regulation, targetedVehicleClass, Class 7 trucks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetedVehicleClass Context triple: [Truck and Bus Regulation, targetedVehicleClass, Class 7 trucks]
-
A.
intendedVehicleClass
chosen
Indicates that one entity is designed or specified to be used with, or is appropriate for, a particular class or category of vehicle.
-
B.
mainVehicleClass
Indicates the primary category or type of vehicle to which an entity chiefly belongs.
-
C.
intendedVehicle
Indicates that one entity is the vehicle that another entity plans or is meant to use.
-
D.
vehicleType
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
E.
vehicleClassServed
Indicates the class or type of vehicle that a service, facility, or operation is designed to accommodate or serve.
- 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_69e75db8bab08190baca80b4a8c315fd |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f657f653448190a945b4751af8507d |
completed | May 2, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 21, 2026, 2:14 p.m.