Triple
T29203869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Haneda – Naha |
E740354
|
entity |
| Predicate | servedByAirportTypeOrigin |
P54051
|
FINISHED |
| Object | 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: hub airport | Statement: [Tokyo Haneda – Naha, servedByAirportTypeOrigin, hub airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedByAirportTypeOrigin Context triple: [Tokyo Haneda – Naha, servedByAirportTypeOrigin, hub airport]
-
A.
servedByAirportInOriginCity
Indicates that the origin city of a trip or route is served by a particular airport.
-
B.
servesAirportType
chosen
Indicates that a transportation service or facility provides service to, or is designated for, a specific type or category of airport.
-
C.
typicalOriginAirportIATA
Indicates the usual or primary origin airport for an entity, identified by its IATA airport code.
-
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.
hasOriginAirport
Indicates that something, typically a flight or journey, departs from or is associated with a specific origin airport.
- 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_69fdb45537288190b6791078d4a6899f |
completed | May 8, 2026, 10 a.m. |
| PD | Predicate disambiguation | batch_69fdb39ad96481908376d7def9fafc13 |
completed | May 8, 2026, 9:57 a.m. |
Created at: April 28, 2026, 12:08 p.m.