Triple
T28813601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 新富士駅 |
E727579
|
entity |
| Predicate | 最寄り空港 |
P4363
|
FINISHED |
| Object | 富士山静岡空港 |
—
|
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: 富士山静岡空港 | Statement: [新富士駅, 最寄り空港, 富士山静岡空港]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 最寄り空港 Context triple: [新富士駅, 最寄り空港, 富士山静岡空港]
-
A.
associatedAirport
Indicates a relationship where an entity is linked or connected to a specific airport, typically as its relevant or corresponding airport.
-
B.
parentAirport
Indicates that one airport serves as the primary or overarching facility from which another, subsidiary or associated airport is derived or managed.
-
C.
airportServed
chosen
Indicates that a particular airport provides service to, or is used for air travel to and from, a given location or area.
-
D.
previousPrimaryAirportFor
Indicates that one airport was formerly the main or primary airport serving a particular location or entity before being replaced by another.
-
E.
associatedAirportLocalName
Indicates the local or native-language name of the airport that is associated with the given 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_69f0319c38948190bca746ad60fd25ba |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f658f163a88190b1dd222eaa0f93ea |
completed | May 2, 2026, 8:05 p.m. |
| PD | Predicate disambiguation | batch_69f65762b5e481908a30ca963dcba4be |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 6:32 a.m.