Triple
T10353584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conservatoire de Paris student orchestra |
E243941
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | training ensemble |
C2760
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: training ensemble Context triple: [Conservatoire de Paris student orchestra, instanceOf, training ensemble]
-
A.
training ship
A training ship is a vessel specifically equipped and operated to provide practical seamanship and maritime education to cadets and trainees at sea.
-
B.
training unit
chosen
A training unit is a structured, self-contained segment of instruction designed to teach specific knowledge, skills, or competencies within a broader training program.
-
C.
deep learning model
A deep learning model is a computational architecture composed of multiple layers of interconnected processing units (neurons) that automatically learn hierarchical representations from data to perform tasks such as classification, prediction, or generation.
-
D.
training division
A training division is an organizational unit responsible for planning, developing, and delivering educational and skill-building programs to employees or members.
-
E.
adaptive learning rate method
An adaptive learning rate method is an optimization technique that automatically adjusts the step size for each parameter during training based on past gradient information to improve convergence speed and stability.
- F. None of above.
Provenance (1 batch)
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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
Created at: April 6, 2026, 11:58 a.m.