Triple
T29596262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naval Air Station Meridian |
E754306
|
entity |
| Predicate | aircraftUsedForTraining |
P162330
|
FINISHED |
| Object | T-45 Goshawk |
—
|
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: T-45 Goshawk | Statement: [Naval Air Station Meridian, aircraftUsedForTraining, T-45 Goshawk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftUsedForTraining Context triple: [Naval Air Station Meridian, aircraftUsedForTraining, T-45 Goshawk]
-
A.
aircraftTrainedOn
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.
usedTrainerAircraft
chosen
Indicates that an entity employed a particular trainer aircraft for training or instructional purposes.
-
C.
hasFixedWingTrainingRole
Indicates that an entity serves in a training capacity specifically related to the operation or use of fixed-wing 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_69f0ef836ac88190bd809dc58b5ec907 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f69dfdda708190be290c7bec205445 |
completed | May 3, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f69d1a37e081908d1d86b90ff502bd |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 28, 2026, 6:18 p.m.