Triple
T24536739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USCG Aviation Training Center Mobile |
E606969
|
entity |
| Predicate | hasAircraftTypeTrained |
P84229
|
FINISHED |
| Object | fixed-wing 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: fixed-wing aircraft | Statement: [USCG Aviation Training Center Mobile, hasAircraftTypeTrained, fixed-wing aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAircraftTypeTrained Context triple: [USCG Aviation Training Center Mobile, hasAircraftTypeTrained, fixed-wing aircraft]
-
A.
hasFlightTrainingActivity
Indicates that an entity is involved in or associated with a flight training activity.
-
B.
hasFixedWingTraining
chosen
Indicates that an entity has received training in operating or working with fixed-wing aircraft.
-
C.
hasFixedWingTrainingRole
Indicates that an entity serves in a training capacity specifically related to the operation or use of fixed-wing aircraft.
-
D.
hasHelicopterTrainingFields
Indicates that an entity provides or includes designated fields or facilities specifically used for helicopter training activities.
-
E.
hasHelicopterTrainingRole
Indicates that an entity holds a role or position specifically related to the training or instruction of helicopter operations.
- 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_69e2c4c90c848190b23c4303620dcaaf |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b0ca8081908d931aec560eae56 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:26 a.m.