Triple
T29203870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Haneda – Naha |
E740354
|
entity |
| Predicate | servedByAirportTypeDestination |
P157746
|
FINISHED |
| Object | regional hub airport |
—
|
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: regional hub airport | Statement: [Tokyo Haneda – Naha, servedByAirportTypeDestination, regional hub airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedByAirportTypeDestination Context triple: [Tokyo Haneda – Naha, servedByAirportTypeDestination, regional hub airport]
-
A.
servesAirportType
Indicates that a transportation service or facility provides service to, or is designated for, a specific type or category of airport.
-
B.
servedByAirportInOriginCity
Indicates that the origin city of a trip or route is served by a particular airport.
-
C.
servesAirport
Indicates that a transportation service or route provides access to and operates for a particular airport.
-
D.
servedByAirportPair
Indicates that a specific pair of airports is connected by at least one service, such as a scheduled flight route, between them.
-
E.
airlineDestinationType
chosen
Indicates the type or category of destination (e.g., domestic, international, hub) associated with an airline’s route or flight.
- 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_69f07cb974108190b7e86ca489a6ebb6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69fdbaa226708190b8ed96e93aad38de |
completed | May 8, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69fdb58b07e48190837e00966de050d4 |
completed | May 8, 2026, 10:06 a.m. |
Created at: April 28, 2026, 12:08 p.m.