Triple
T12507953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Squadron Officer School |
E298998
|
entity |
| Predicate | levelWithinPME |
P105328
|
FINISHED |
| Object | company-grade officer education |
—
|
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: company-grade officer education | Statement: [Squadron Officer School, levelWithinPME, company-grade officer education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: levelWithinPME Context triple: [Squadron Officer School, levelWithinPME, company-grade officer education]
-
A.
levels
Indicates that one entity adjusts, equalizes, or smooths out the height, intensity, or degree of another entity.
-
B.
enrollmentLevel
Indicates the degree or status of participation an entity has in a particular enrollment context (such as a program, course, or service).
-
C.
levelServed
Indicates that a particular service, function, or resource is provided or made available at a specified level or tier.
-
D.
meetsAtLevel
Indicates that two or more entities encounter or interact with each other at a specific hierarchical, structural, or progression level.
-
E.
commonLevel
Indicates that two or more entities share the same level, rank, or hierarchical position within a given system or structure.
- F. None of above. chosen
Provenance (4 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954b867dc8190af8a70f797e4d133 |
completed | April 10, 2026, 7:51 p.m. |
| PD | Predicate disambiguation | batch_69d954096af88190b6be81b008c82139 |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d954b715fc819091fa84430be46273 |
completed | April 10, 2026, 7:51 p.m. |
Created at: April 8, 2026, 9:57 p.m.