Triple
T12625765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Air Force Senior Noncommissioned Officer Academy |
E301508
|
entity |
| Predicate | studentRankRange |
P34817
|
FINISHED |
| Object | master sergeant |
—
|
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: master sergeant | Statement: [Air Force Senior Noncommissioned Officer Academy, studentRankRange, master sergeant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studentRankRange Context triple: [Air Force Senior Noncommissioned Officer Academy, studentRankRange, master sergeant]
-
A.
rankRange
Indicates that an entity’s rank falls within a specified minimum and maximum range.
-
B.
rankOfTypicalStudents
chosen
Indicates the usual or most common rank or standing that students hold within a given group or context.
-
C.
gradeRange
Indicates the span of grades or scores that an item, performance, or entity falls within.
-
D.
gradeRank
Indicates the relative academic standing or position of an entity within a graded or ranked group based on performance or scores.
-
E.
gradeRangeStart
Indicates the lower boundary value at which a particular grade or grading interval begins.
- 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_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. |
Created at: April 9, 2026, 5:14 p.m.