Triple
T15292373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VAL |
E365558
|
entity |
| Predicate | typicalTrainConfiguration |
P42282
|
FINISHED |
| Object | 2-car trainsets |
—
|
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: 2-car trainsets | Statement: [VAL, typicalTrainConfiguration, 2-car trainsets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTrainConfiguration Context triple: [VAL, typicalTrainConfiguration, 2-car trainsets]
-
A.
trainConfiguration
Indicates the specific arrangement and composition of train elements (such as locomotives and cars) used together for a particular operation or service.
-
B.
locomotiveConfiguration
Indicates the specific arrangement and type of power and running units (e.g., wheel or axle layout) that define how a locomotive is configured.
-
C.
trainTypeUsed
Indicates that a specific type or category of train is employed or operated in a given context or service.
-
D.
maintainsTrainsFor
Indicates that one entity is responsible for servicing, repairing, or otherwise keeping trains operational for another entity.
-
E.
vehiclesPerTrain
chosen
Indicates the number of vehicles that are attached to or make up a single train.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03680b60c8190a3ea54a9d34c8105 |
completed | April 16, 2026, 1:08 a.m. |
| PD | Predicate disambiguation | batch_69deca935e2c8190b640987ddfc542b9 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:15 a.m.