Triple
T32179598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Air Force enlisted rank structure |
E821944
|
entity |
| Predicate | lowestPayGrade |
P6063
|
FINISHED |
| Object | E-1 |
—
|
NE NERFINISHED |
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-1 | Statement: [United States Air Force enlisted rank structure, lowestPayGrade, E-1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lowestPayGrade Context triple: [United States Air Force enlisted rank structure, lowestPayGrade, E-1]
-
A.
lowestGrade
Indicates that one entity has the smallest or worst grade value compared to all other relevant entities in a given context.
-
B.
lowestRank
chosen
Indicates that the subject has the least or worst rank in an ordered set compared to all other related entities.
-
C.
lowestCategory
Indicates that an entity belongs to the most specific or least general category within a classification hierarchy.
-
D.
lowestOrder
Indicates that one entity has the smallest or minimal order, rank, or priority relative to a set of comparable entities.
-
E.
lowestScore
Indicates that the associated value is the smallest (minimum) score among a set of scores.
- 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_69f3490755288190aee11740a34862f9 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6ba7bfcd0819099d652fc7db158b8 |
completed | May 3, 2026, 3:01 a.m. |
| PD | Predicate disambiguation | batch_69f6b3aa892481908d29283a074e6722 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:34 a.m.