Triple
T33093829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Command Sergeant Major (USA) |
E846854
|
entity |
| Predicate | pay grade |
P7397
|
FINISHED |
| Object | E-9 |
—
|
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: E-9 | Statement: [Command Sergeant Major (USA), pay grade, E-9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pay grade Context triple: [Command Sergeant Major (USA), pay grade, E-9]
-
A.
payGrade
chosen
Indicates the level or category of compensation assigned to an entity, typically reflecting its rank, role, or seniority in a pay structure.
-
B.
payGradeComparison
Indicates that the relative pay grade or salary level between two entities is being compared (e.g., one is higher, lower, or equal to the other).
-
C.
payScaleNumber
Indicates the specific numeric level or grade assigned to an entity within a pay scale or salary structure.
-
D.
payScale
Indicates the compensation level or salary range assigned to an entity, typically reflecting its relative pay or grade within a structured system.
-
E.
salary
Indicates the amount of monetary compensation an entity receives, typically on a regular basis, for work or services performed.
- 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_69f3495590dc8190aa04f3dec74ce976 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d27120988190aacec621cf2bf0e8 |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:26 a.m.