Triple
T32683810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | E6 series Shinkansen |
E835661
|
entity |
| Predicate | serviceStartRoute |
P66864
|
FINISHED |
| Object | Tokyo–Akita |
—
|
NE NERFINISHED |
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: Tokyo–Akita | Statement: [E6 series Shinkansen, serviceStartRoute, Tokyo–Akita]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceStartRoute Context triple: [E6 series Shinkansen, serviceStartRoute, Tokyo–Akita]
-
A.
serviceRoute
chosen
Indicates that a service (such as a transport or delivery operation) follows or is assigned to a particular route.
-
B.
serviceStartLocation
Indicates the place where a service or operation is initiated or begins.
-
C.
serviceStartContext
Indicates the circumstances or conditions under which a service begins or is initiated.
-
D.
serviceUseCase
Indicates that an entity is used as a service to fulfill or support a particular use case or functional scenario.
-
E.
serviceToState
Indicates a relationship where an entity provides service, assistance, or functional support to a state or governmental body.
- 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_69f3493211388190993801216afbc2a7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 1, 2026, 1:09 a.m.