Triple
T28813529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 濃尾平野 |
E727577
|
entity |
| Predicate | 関連空港 |
P58803
|
FINISHED |
| Object | 中部国際空港の後背地 |
—
|
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: 中部国際空港の後背地 | Statement: [濃尾平野, 関連空港, 中部国際空港の後背地]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関連空港 Context triple: [濃尾平野, 関連空港, 中部国際空港の後背地]
-
A.
associatedAirport
chosen
Indicates a relationship where an entity is linked or connected to a specific airport, typically as its relevant or corresponding airport.
-
B.
associatedHubAirport
Indicates that one entity serves as a primary or hub airport functionally linked to the other entity.
-
C.
relatedAirfield
Indicates that there is an association or connection between an entity and a specific airfield, such as operational use, location, or administrative linkage.
-
D.
associatedWithAirportName
Indicates a relationship where an entity is linked or connected to a specific airport by its name.
-
E.
associatedAirportServes
Indicates that a given airport provides service to, or is used by, the associated entity (such as a city, region, or facility).
- 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.