Triple
T2127124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sergeant (USSF enlisted rank) |
E46452
|
entity |
| Predicate | payGradeSystem |
P7397
|
FINISHED |
| Object | United States military pay grades |
—
|
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: United States military pay grades | Statement: [Sergeant (USSF enlisted rank), payGradeSystem, United States military pay grades]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: payGradeSystem Context triple: [Sergeant (USSF enlisted rank), payGradeSystem, United States military pay grades]
-
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.
salaryType
Indicates the classification or structure of compensation associated with an entity, such as whether pay is salaried, hourly, commission-based, or another type.
-
C.
rankGrade
Indicates the grade or level assigned to an entity within a ranking or evaluation system.
-
D.
gradingPolicy
Indicates the rules or criteria that determine how performance or work is evaluated and assigned grades.
-
E.
gradeStructure
Indicates the hierarchical organization or breakdown of grades or scoring components within an evaluation system.
- 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_69a88a1626548190ae59a5028c3baa8e |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbb75033881909b16659fc73945ef |
completed | March 7, 2026, 5:45 a.m. |
| PD | Predicate disambiguation | batch_69abb7bd86cc8190938ef06c1ed6d969 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:44 p.m.