Triple
T12762021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MCI D-Series coaches |
E305017
|
entity |
| Predicate | typicalAxleConfiguration |
P85302
|
FINISHED |
| Object | two-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: two-axle | Statement: [MCI D-Series coaches, typicalAxleConfiguration, two-axle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAxleConfiguration Context triple: [MCI D-Series coaches, typicalAxleConfiguration, two-axle]
-
A.
hasAxleCount
chosen
Indicates the number of axles that an object (typically a vehicle or rolling stock) possesses.
-
B.
numberOfAxlesDriven
Indicates the count of axles on a vehicle that are actively powered or driven by the propulsion system.
-
C.
axleLoad
Indicates the amount of weight or force that is supported or exerted by a single axle in a vehicle or structure.
-
D.
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.
-
E.
numberOfRoadWheelsPerSide
Indicates the count of road wheels present on each side of a vehicle or similar wheeled system.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d8e44188190840cd23d380bf23d |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96409739881909174ba005a986cb5 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:28 p.m.