Triple
T828292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UK Cadet Forces |
E17904
|
entity |
| Predicate | trainingStyle |
P16019
|
FINISHED |
| Object | structured syllabus-based 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: structured syllabus-based training | Statement: [UK Cadet Forces, trainingStyle, structured syllabus-based training]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingStyle Context triple: [UK Cadet Forces, trainingStyle, structured syllabus-based training]
-
A.
trainingFormat
Indicates the specific method or medium through which training is delivered or conducted.
-
B.
trainingMethod
chosen
Indicates the specific approach, technique, or procedure used to train an entity (such as a person, model, or system).
-
C.
trainingSystem
Indicates a system or framework used to train, instruct, or develop skills or knowledge in a target entity.
-
D.
trainingParadigm
Indicates the specific methodological framework or approach used to train an entity (such as a model, system, or agent).
-
E.
training
Indicates that one entity is teaching, coaching, or otherwise helping another entity acquire or improve a skill, behavior, or capability.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ab99b1e48190afad1f073348b29a |
completed | March 1, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69a4aa79a6488190a634388e071ed9b7 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.