Triple
T32161206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avarua, Rarotonga |
E821431
|
entity |
| Predicate | mainAirportServing |
P151946
|
FINISHED |
| Object | Rarotonga International Airport |
—
|
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: Rarotonga International Airport | Statement: [Avarua, Rarotonga, mainAirportServing, Rarotonga International Airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainAirportServing Context triple: [Avarua, Rarotonga, mainAirportServing, Rarotonga International Airport]
-
A.
airportServed
Indicates that a particular airport provides service to, or is used for air travel to and from, a given location or area.
-
B.
mainAccessAirport
chosen
Indicates that one location serves as the primary airport providing access to another place or region.
-
C.
airportServesAs
Indicates that an airport functions in a particular role or capacity (such as primary, secondary, or hub) for a specified area, organization, or service.
-
D.
associatedAirportServes
Indicates that a given airport provides service to, or is used by, the associated entity (such as a city, region, or facility).
-
E.
hasPrimaryAirportRole
Indicates that an entity holds the main or principal functional role associated with an 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_69f34905e098819082191a6922a6d607 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6f8164698819090c1b471f1caa4c6 |
completed | May 3, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69f6f6619404819084662aef1238261c |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 12:32 a.m.