Triple
T23636487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kikuna Depot |
E583761
|
entity |
| Predicate | servicesRollingStockType |
P1305
|
FINISHED |
| Object | electric multiple 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: electric multiple unit | Statement: [Kikuna Depot, servicesRollingStockType, electric multiple unit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servicesRollingStockType Context triple: [Kikuna Depot, servicesRollingStockType, electric multiple unit]
-
A.
passengerRollingStock
Indicates that the rolling stock is designed or used for carrying passengers rather than freight or other purposes.
-
B.
rollingStockType
chosen
Indicates the specific category or type of railway rolling stock associated with an entity (e.g., locomotive, passenger car, freight wagon).
-
C.
ownedRollingStock
Indicates that one entity possesses or has ownership rights over specific rolling stock (such as trains, railcars, or locomotives).
-
D.
eraOfRollingStock
Indicates the historical time period or service era during which a particular rolling stock type was in use.
-
E.
operatedRollingStockClass
Indicates that an entity (such as a company or operator) has operated a specific class or type of rolling stock (e.g., trains or rail vehicles).
- 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_69e248fe1c2c8190ac914d2442ff3d26 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b1ed03148190a14b3c81ebf7ed99 |
completed | April 29, 2026, 7:23 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:47 p.m.