Triple
T470646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Army Cyber School |
E8546
|
entity |
| Predicate | hasTypeOfTraining |
P10219
|
FINISHED |
| Object | initial entry training |
—
|
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: initial entry training | Statement: [U.S. Army Cyber School, hasTypeOfTraining, initial entry training]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfTraining Context triple: [U.S. Army Cyber School, hasTypeOfTraining, initial entry training]
-
A.
hasEducationalProgram
Indicates that an entity offers, runs, or is associated with a specific educational program.
-
B.
trainingInstitution
Indicates that one entity serves as the institution or organization where another entity receives training or education.
-
C.
trainingSystem
Indicates a system or framework used to train, instruct, or develop skills or knowledge in a target entity.
-
D.
typicalTraining
chosen
Indicates that an entity commonly undergoes or is associated with a standard or usual form of training in relation to another entity or context.
-
E.
hasCoachedFor
Indicates that one entity has served in a coaching role for another entity, such as a team, organization, or individual.
- 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_69a2e7f3aeb48190a19453e3a043f486 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efef8b788190857ebf66df562d59 |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2edecefb081908331ef8b9edf6636 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.