Triple
T29293805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miyazaki–Tokyo Haneda |
E742760
|
entity |
| Predicate | airportOfOriginRegion |
P75280
|
FINISHED |
| Object | Miyazaki Prefecture |
—
|
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: Miyazaki Prefecture | Statement: [Miyazaki–Tokyo Haneda, airportOfOriginRegion, Miyazaki Prefecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportOfOriginRegion Context triple: [Miyazaki–Tokyo Haneda, airportOfOriginRegion, Miyazaki Prefecture]
-
A.
associatedAirportGeographicRegion
chosen
Indicates that an airport is located within or linked to a specific geographic region.
-
B.
hasOriginAirport
Indicates that something, typically a flight or journey, departs from or is associated with a specific origin airport.
-
C.
placeOfArrival
Indicates the location at which an entity or person arrives at the end of a journey, movement, or transfer.
-
D.
hasOriginAirportCity
Indicates that an entity (such as a flight or trip) departs from or is associated with a specific origin airport located in a given city.
-
E.
hasAirportCodeRegion
Indicates that an airport code is associated with, or belongs to, a specific geographic or administrative region.
- 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_69f0912323c48190b9a24ef8cf359225 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f6b903538481909cffcb6cc1cc0e70 |
completed | May 3, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
Created at: April 28, 2026, 1:04 p.m.