Triple
T16696080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryukyu Air Commuter |
E405718
|
entity |
| Predicate | usesAircraftCategory |
P45618
|
FINISHED |
| Object | turboprop aircraft |
—
|
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: turboprop aircraft | Statement: [Ryukyu Air Commuter, usesAircraftCategory, turboprop aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAircraftCategory Context triple: [Ryukyu Air Commuter, usesAircraftCategory, turboprop aircraft]
-
A.
usedByAircraftType
Indicates that something (such as equipment, infrastructure, or a procedure) is employed or operated by a specific type or category of aircraft.
-
B.
usesCarrierAircraft
Indicates that one entity employs or operates aircraft that are designed to be launched from and recovered by an aircraft carrier.
-
C.
typicalAircraftTypeCategory
chosen
Indicates the general class or category of aircraft type that is most commonly associated with or used in a given context.
-
D.
usedByAircraftRegisteredIn
Indicates that something (such as equipment, a system, or a facility) is utilized by aircraft that are registered in a specified jurisdiction or registry.
-
E.
usedOnAircraftName
Indicates that something is employed or applied on an aircraft identified by a specific name.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37eadc35881909fb0cc405a0e2fae |
completed | April 18, 2026, 12:53 p.m. |
| PD | Predicate disambiguation | batch_69e319bc73908190a0e38bc926b31f10 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:19 a.m.