Triple
T25854051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 56th Fighter Wing |
E651292
|
entity |
| Predicate | aircraftTrainedOn |
P159831
|
FINISHED |
| Object | F-16 Fighting Falcon |
—
|
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: F-16 Fighting Falcon | Statement: [56th Fighter Wing, aircraftTrainedOn, F-16 Fighting Falcon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftTrainedOn Context triple: [56th Fighter Wing, aircraftTrainedOn, F-16 Fighting Falcon]
-
A.
aircraftTrainedOn
chosen
Indicates that an aircraft has been used as the platform or subject for training a person or crew in its operation or related skills.
-
B.
hasFixedWingTrainingRole
Indicates that an entity serves in a training capacity specifically related to the operation or use of fixed-wing aircraft.
-
C.
aircraftFlown
Indicates that an entity (typically a person or organization) operates or pilots a particular aircraft.
-
D.
aircraftTypesUsedOn
Indicates the types or models of aircraft that are used on or assigned to a particular route, service, operation, or context.
-
E.
operatesAircraftFor
Indicates that one entity pilots or controls an aircraft on behalf of, or in service to, another entity.
- 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_69e7ab39035c8190be15c8aaee1bb858 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6023d27808190a994fc80ff557c89 |
completed | May 2, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fba5248190945acf1561280799 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 22, 2026, 7:59 a.m.