Triple
T34207311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul W. Airey Noncommissioned Officer Academy |
E877547
|
entity |
| Predicate | associatedRankCategory |
P11443
|
FINISHED |
| Object | noncommissioned officers |
—
|
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: noncommissioned officers | Statement: [Paul W. Airey Noncommissioned Officer Academy, associatedRankCategory, noncommissioned officers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedRankCategory Context triple: [Paul W. Airey Noncommissioned Officer Academy, associatedRankCategory, noncommissioned officers]
-
A.
associatedWithRank
Indicates a relationship where an entity is linked to a specific rank, level, or hierarchical position.
-
B.
hasRankingCategory
Indicates that an entity is associated with a particular ranking category or tier within an ordered classification system.
-
C.
hasRankCategory
chosen
Indicates that an entity is assigned to a particular rank-based classification or level within an ordered hierarchy.
-
D.
rankingCategory
Indicates the classification or type of ranking under which an entity is evaluated or ordered.
-
E.
includesRankCategory
Indicates that one entity’s set of ranks or classifications contains or encompasses a particular rank category.
- 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_69f349aff5f0819096275315abea5344 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:55 a.m.