Triple
T23676766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miyahara Station |
E584898
|
entity |
| Predicate | nearbyMajorHub |
P99506
|
FINISHED |
| Object | Ōmiya Station |
—
|
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: Ōmiya Station | Statement: [Miyahara Station, nearbyMajorHub, Ōmiya Station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyMajorHub Context triple: [Miyahara Station, nearbyMajorHub, Ōmiya Station]
-
A.
nearestMajorTransportHub
chosen
Indicates that one location is the closest significant transportation center (such as a major train station, airport, or bus terminal) to another location.
-
B.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
C.
nearestMajorMetro
Indicates the relationship where a given location is associated with the closest large metropolitan area to it.
-
D.
nearbyMajorRoad
Indicates that one entity is located close to a significant or heavily used road.
-
E.
infrastructureNearby
Indicates that one entity is located close to another entity that serves as infrastructure (such as roads, utilities, or public facilities).
- 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_69e24901f7c08190909fd727632e823d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b4f40c9081908ef0cddb6f0392da |
completed | April 29, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f118dd13008190a8799b4e9cadbd79 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:51 p.m.