Triple
T29735643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Training Air Wing TWO |
E752449
|
entity |
| Predicate | hasTrainingPipelineOutcome |
P95646
|
FINISHED |
| Object | designation as naval aviator |
—
|
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: designation as naval aviator | Statement: [Training Air Wing TWO, hasTrainingPipelineOutcome, designation as naval aviator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainingPipelineOutcome Context triple: [Training Air Wing TWO, hasTrainingPipelineOutcome, designation as naval aviator]
-
A.
hasTrainingPipelineFrom
chosen
Indicates that something is produced or derived as the result of a specified training pipeline or process.
-
B.
hasTrained
Indicates that one entity has provided training or instruction to another entity.
-
C.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
D.
trainingPipelineIncludes
Indicates that a training pipeline contains or incorporates a specific component, step, or resource as part of its overall process.
-
E.
hasTrainingFunction
Indicates that one entity serves as a training function or mechanism for 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_69f0d62a36a88190bf860f00da433ff8 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fe031bc6208190860099aef72d8dcb |
completed | May 8, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69fe014c8b388190b5d4e0cb95ee2be5 |
completed | May 8, 2026, 3:29 p.m. |
Created at: April 28, 2026, 7:45 p.m.