Triple
T12625768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Air Force Senior Noncommissioned Officer Academy |
E301508
|
entity |
| Predicate | studentComponent |
P105975
|
FINISHED |
| Object | active duty |
—
|
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: active duty | Statement: [Air Force Senior Noncommissioned Officer Academy, studentComponent, active duty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studentComponent Context triple: [Air Force Senior Noncommissioned Officer Academy, studentComponent, active duty]
-
A.
studentModel
Indicates that one entity serves as a model or example for a student in the context of learning or education.
-
B.
studentsWing
Indicates a relationship where a particular wing, section, or area is designated for or associated with students.
-
C.
studentSection
Indicates a relationship where a student is enrolled in or associated with a particular course section.
-
D.
studentRecorder
Indicates that one entity serves as the recorder (note-taker or documenter) for another entity in an educational or learning context.
-
E.
studentOrAssistant
Indicates that an individual has the role of either a student or an assistant in a given context or relationship.
- F. None of above. chosen
Provenance (4 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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617b07ec8190b714f04ae6654060 |
completed | April 10, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69d960b195108190ac25bd95e644ace4 |
completed | April 10, 2026, 8:42 p.m. |
| PDg | Predicate description generation | batch_69d96179c7648190a05a13991d62bebb |
completed | April 10, 2026, 8:45 p.m. |
Created at: April 9, 2026, 5:14 p.m.