Triple
T37893996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | E7 series Shinkansen |
E945223
|
entity |
| Predicate | firstOperatorServiceArea |
—
|
GENERATED |
| Object | Tokyo–Nagano |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstOperatorServiceArea Context triple: [E7 series Shinkansen, firstOperatorServiceArea, Tokyo–Nagano]
-
A.
hasPrimaryServiceArea
Indicates that an entity is associated with a main geographic or functional area in which it primarily provides its services.
-
B.
areaOfService
chosen
Indicates the geographic or functional region within which a service is provided or applicable.
-
C.
serviceAreaName
Indicates the designated name of the geographic or functional area that a service covers or operates within.
-
D.
typicalOperatorService
Indicates that an entity commonly performs or provides a particular operational service in a standard or expected manner.
-
E.
primaryOperator
Indicates that an entity serves as the main or leading operator responsible for performing or overseeing a specified operation or process in relation to another entity.
- F. None of above.
Provenance (1 batch)
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_69f76ef0e8708190987c7254ed8c7abe |
completed | May 3, 2026, 3:51 p.m. |
Created at: May 3, 2026, 4:19 p.m.