Triple
T6449795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melbourne Orlando International Airport |
E139833
|
entity |
| Predicate | isGeneralAviationAirport |
P24735
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Melbourne Orlando International Airport, isGeneralAviationAirport, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isGeneralAviationAirport Context triple: [Melbourne Orlando International Airport, isGeneralAviationAirport, true]
-
A.
isCivilAirport
Indicates that an airport is designated and used primarily for civilian (non-military) aviation operations.
-
B.
isPublicAirport
Indicates that an airport is open for use by the general public rather than restricted to private or military operations.
-
C.
hasGeneralAviationActivity
Indicates that an entity is involved in or supports non-commercial, private, or recreational aviation operations.
-
D.
hasGeneralAviationFacilities
chosen
Indicates that a location or airport provides facilities and services specifically for general aviation operations.
-
E.
isRegionalAirport
Indicates that an airport serves a specific region or local area rather than functioning as a major national or international hub.
- 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_69c008b301948190a35854e5284dc822 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c069b2c7bc81908c683ec22cad9628 |
completed | March 22, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69c0673b44148190aed70084f0ff4992 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:47 p.m.