Triple
T11934268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 文京区 |
E283998
|
entity |
| Predicate | wardOfficeNearestStation |
P26735
|
FINISHED |
| Object | 後楽園駅 |
—
|
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: 後楽園駅 | Statement: [文京区, wardOfficeNearestStation, 後楽園駅]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wardOfficeNearestStation Context triple: [文京区, wardOfficeNearestStation, 後楽園駅]
-
A.
operatorOfNearestStation
Indicates that an entity is the organization or operator responsible for managing the station that is geographically closest to a given reference point or entity.
-
B.
nearestEntranceStation
Indicates that one station is the closest entrance station to a given location or entity compared to all other candidate stations.
-
C.
nearestSuburbanRailwayStation
Indicates the relationship where a given place is associated with the suburban railway station that is geographically closest to it.
-
D.
nearestUndergroundStation
chosen
Indicates the relationship where a specific underground (subway/metro) station is the closest one in distance to a given location or entity.
-
E.
nearestPassengerRailStation
Indicates that one entity is the closest passenger rail station in distance to another entity.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90306fcf48190a963d2d1932288d1 |
completed | April 10, 2026, 2:02 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3af0188190bfb22be5c97b3349 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.