Triple
T16384633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Studebaker US6 truck |
E397888
|
entity |
| Predicate | frontAxleConfiguration |
P123186
|
FINISHED |
| Object | single steering axle |
—
|
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: single steering axle | Statement: [Studebaker US6 truck, frontAxleConfiguration, single steering axle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frontAxleConfiguration Context triple: [Studebaker US6 truck, frontAxleConfiguration, single steering axle]
-
A.
frontEnginePosition
Indicates that the engine of a vehicle is located at the front portion of the vehicle.
-
B.
hasAxleCount
Indicates the number of axles that an object (typically a vehicle or rolling stock) possesses.
-
C.
rearAxleRatio
Indicates the numerical gear ratio between the driveshaft and the rear axle, describing how many driveshaft rotations are required for one rotation of the rear wheels.
-
D.
wheelbase
Indicates the distance between the centers of the front and rear wheels of a vehicle.
-
E.
axleLoad
Indicates the amount of weight or force that is supported or exerted by a single axle in a vehicle or structure.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e3263c60088190b85a8c02bc3ef315 |
completed | April 18, 2026, 6:35 a.m. |
| PD | Predicate disambiguation | batch_69e226f94dd48190b7b8e0e983738a67 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:08 a.m.