Triple
T7196541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AC-10 |
E168628
|
entity |
| Predicate | driveWheelArrangement |
P5627
|
FINISHED |
| Object | eight driving wheels per engine unit |
—
|
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: eight driving wheels per engine unit | Statement: [AC-10, driveWheelArrangement, eight driving wheels per engine unit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: driveWheelArrangement Context triple: [AC-10, driveWheelArrangement, eight driving wheels per engine unit]
-
A.
wheelCount
Indicates the number of wheels associated with a given entity.
-
B.
wheelArrangementSystem
chosen
Indicates the specific configuration or system by which the wheels of a vehicle or rolling stock are arranged and organized.
-
C.
numberOfRoadWheelsPerSide
Indicates the count of road wheels present on each side of a vehicle or similar wheeled system.
-
D.
numberOfWheels
Indicates the quantity of wheels that an entity possesses or is associated with.
-
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_69c68a5376748190bb500f03df86e93e |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6e928ecdc8190a7f3feaf6d28781b |
completed | March 27, 2026, 8:31 p.m. |
| PD | Predicate disambiguation | batch_69c6e752385c819096fbab55566ee2a8 |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:51 p.m.