Triple
T4894562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Staff Sergeant Instructor |
E109643
|
entity |
| Predicate | hasRankClass |
P11443
|
FINISHED |
| Object | senior non-commissioned officer |
—
|
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: senior non-commissioned officer | Statement: [Staff Sergeant Instructor, hasRankClass, senior non-commissioned officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRankClass Context triple: [Staff Sergeant Instructor, hasRankClass, senior non-commissioned officer]
-
A.
hasRankCategory
chosen
Indicates that an entity is assigned to a particular rank-based classification or level within an ordered hierarchy.
-
B.
hasRankContext
Indicates that an entity’s rank or ordering is defined, interpreted, or constrained within a specific contextual framework or situation.
-
C.
hasRankVariant
Indicates that one entity is an alternative or variant form of another entity’s rank or hierarchical level.
-
D.
hasRankingCategory
Indicates that an entity is associated with a particular ranking category or tier within an ordered classification system.
-
E.
hasRankingUnit
Indicates that one entity is associated with a specific unit or scale used to express its ranking or ordered position.
- 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_69bd4410bbf88190aad50d2451c863d6 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ffabccc81909115ece1b04e2061 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2e7b5c8190b8bf9d616dfa24f0 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:28 p.m.