Triple
T37026135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lulu Island–Sea Island area |
E916359
|
entity |
| Predicate | hasAirportInfrastructureOn |
P140135
|
FINISHED |
| Object | Sea Island |
—
|
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: Sea Island | Statement: [Lulu Island–Sea Island area, hasAirportInfrastructureOn, Sea Island]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAirportInfrastructureOn Context triple: [Lulu Island–Sea Island area, hasAirportInfrastructureOn, Sea Island]
-
A.
hasAirportAccessTo
Indicates that one location or entity has direct access to another via an airport connection or service.
-
B.
hasInternationalAirport
Indicates that a place possesses an airport that handles international flights and services cross-border air traffic.
-
C.
hasRunwaysAt
Indicates that a location or facility possesses one or more runways situated at that place.
-
D.
hasAirportTransitSystem
Indicates that an airport is equipped with a dedicated transit system for moving passengers or goods between its terminals, facilities, or areas.
-
E.
hasLandingFacilities
chosen
Indicates that a location or structure is equipped with facilities that allow aircraft or other vehicles to land there.
- 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_69f76e92c7648190bcfa277f64c71a21 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb154c0fe08190a2e41e7a29b6055f |
completed | May 6, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f9fecc005c8190be082a8689193745 |
completed | May 5, 2026, 2:29 p.m. |
Created at: May 3, 2026, 4:14 p.m.