Triple
T5708220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 3 Canadian Forces Flying Training School |
E125837
|
entity |
| Predicate | usesTrainingAircraft |
P60836
|
FINISHED |
| Object | turboprop trainer 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 trainer aircraft | Statement: [3 Canadian Forces Flying Training School, usesTrainingAircraft, turboprop trainer aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTrainingAircraft Context triple: [3 Canadian Forces Flying Training School, usesTrainingAircraft, turboprop trainer aircraft]
-
A.
hasFixedWingTrainingRole
Indicates that an entity serves in a training capacity specifically related to the operation or use of fixed-wing aircraft.
-
B.
hasFlightTrainingActivity
chosen
Indicates that an entity is involved in or associated with a flight training activity.
-
C.
usesCarrierAircraft
Indicates that one entity employs or operates aircraft that are designed to be launched from and recovered by an aircraft carrier.
-
D.
hasHelicopterTrainingRole
Indicates that an entity holds a role or position specifically related to the training or instruction of helicopter operations.
-
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_69c0082d6fe48190b777fb383769e5c8 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0248ab6a88190be17bdc32c36e5cb |
completed | March 22, 2026, 5:19 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:45 p.m.