Triple
T18520815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USRA 2-6-6-2 articulated locomotive |
E452576
|
entity |
| Predicate | trailingWheels |
P19380
|
FINISHED |
| Object | two wheels |
—
|
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 wheels | Statement: [USRA 2-6-6-2 articulated locomotive, trailingWheels, two wheels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trailingWheels Context triple: [USRA 2-6-6-2 articulated locomotive, trailingWheels, two wheels]
-
A.
hasTrailingWheelArrangement
Indicates that an entity (typically a vehicle) possesses a specific configuration of wheels located at its rear or trailing end.
-
B.
numberOfWheels
chosen
Indicates the quantity of wheels that an entity possesses or is associated with.
-
C.
hasLeadingWheelArrangement
Indicates the specific configuration of the leading (front) wheels in a vehicle’s or locomotive’s wheel arrangement.
-
D.
numberOfRoadWheelsPerSide
Indicates the count of road wheels present on each side of a vehicle or similar wheeled system.
-
E.
wheelType
Indicates the specific kind or category of wheel associated with an entity.
- 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_69d8d386df84819092355ebb260d848e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5338db5e4819086503a2176dfe499 |
completed | April 19, 2026, 7:57 p.m. |
| PD | Predicate disambiguation | batch_69e469e0025c81908f16ed4f922674af |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:37 a.m.