Triple
T14249224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 赤坂御用地 |
E353212
|
entity |
| Predicate | 交通最寄りエリア |
P35909
|
FINISHED |
| Object | 赤坂見附周辺 |
—
|
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: 赤坂見附周辺 | Statement: [赤坂御用地, 交通最寄りエリア, 赤坂見附周辺]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 交通最寄りエリア Context triple: [赤坂御用地, 交通最寄りエリア, 赤坂見附周辺]
-
A.
hasNearbyTransportationCorridor
Indicates that an entity is located close to a significant transportation route or corridor, such as a road, railway, or transit line.
-
B.
transportationRegion
chosen
Indicates that one entity serves as, or is associated with, a geographic region relevant to the transportation activities or coverage of another entity.
-
C.
rankInNYCAreaByTraffic
Indicates the position of an entity in an ordered list of entities in the New York City area, sorted by the amount of traffic they receive.
-
D.
transportFocus
Indicates that an entity is the primary object or subject of a transportation action or movement event.
-
E.
nearJunctionOf
Indicates that one entity is located close to the point where two or more linear features (such as roads, tracks, or paths) meet or intersect.
- 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6295ef9081909cfb0c1283bca21a |
completed | April 14, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69de05c09b7881908acbca18bd7d997c |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:08 a.m.