Triple
T29604771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KAvZ |
E754547
|
entity |
| Predicate | hasVehicleLayout |
P5253
|
FINISHED |
| Object | front-engine buses |
—
|
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: front-engine buses | Statement: [KAvZ, hasVehicleLayout, front-engine buses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVehicleLayout Context triple: [KAvZ, hasVehicleLayout, front-engine buses]
-
A.
vehicleLayout
chosen
Indicates how the components or seating within a vehicle are arranged or configured relative to each other.
-
B.
hasVehicleDeck
Indicates that something (typically a vessel or structure) includes a dedicated deck or level designed for carrying or transporting vehicles.
-
C.
hasLeadingWheelArrangement
Indicates the specific configuration of the leading (front) wheels in a vehicle’s or locomotive’s wheel arrangement.
-
D.
hasAxleConfiguration
Indicates that an entity is associated with a specific arrangement or configuration of its axles.
-
E.
hasCarConfiguration
Indicates that an entity is associated with a specific car configuration, detailing how the car is set up or specified.
- 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_69f0ef84e5d08190a0df17f5930ceed3 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 28, 2026, 6:24 p.m.