Triple
T10411164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sir Haydn |
E245391
|
entity |
| Predicate | hasDrivingWheelArrangement |
P5627
|
FINISHED |
| Object | 0-4-0 coupled wheels with trailing 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: 0-4-0 coupled wheels with trailing axle | Statement: [Sir Haydn, hasDrivingWheelArrangement, 0-4-0 coupled wheels with trailing axle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDrivingWheelArrangement Context triple: [Sir Haydn, hasDrivingWheelArrangement, 0-4-0 coupled wheels with trailing axle]
-
A.
wheelArrangementSystem
chosen
Indicates the specific configuration or system by which the wheels of a vehicle or rolling stock are arranged and organized.
-
B.
numberOfAxlesDriven
Indicates the count of axles on a vehicle that are actively powered or driven by the propulsion system.
-
C.
hasAxleCount
Indicates the number of axles that an object (typically a vehicle or rolling stock) possesses.
-
D.
numberOfRoadWheelsPerSide
Indicates the count of road wheels present on each side of a vehicle or similar wheeled system.
-
E.
numberOfWheels
Indicates the quantity of wheels that an entity possesses or is associated with.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9fc72d081908d81c71133973daf |
completed | April 7, 2026, 11:26 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb6f160819090040644a12395ec |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:09 p.m.