Triple
T18724937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | neural tangent kernel |
E457875
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | theoretical construct in machine learning |
C324
|
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: theoretical construct in machine learning Context triple: [neural tangent kernel, instanceOf, theoretical construct in machine learning]
-
A.
machine learning paradigm
A machine learning paradigm is a conceptual framework that defines how models learn from data, including the assumptions, learning objectives, and training procedures that guide the development and application of algorithms.
-
B.
learning theory
Learning theory is the conceptual framework that explains how knowledge and skills are acquired, processed, retained, and applied through experience, instruction, and practice.
-
C.
theoretical model
chosen
A theoretical model is an abstract, simplified representation of a system or phenomenon used to explain, predict, or understand its behavior based on underlying principles and assumptions.
-
D.
machine learning framework
A machine learning framework is a software library or platform that provides tools, abstractions, and workflows to design, train, evaluate, and deploy machine learning models efficiently.
-
E.
machine learning research institute
A machine learning research institute is an organization dedicated to advancing the theory, algorithms, and applications of machine learning through systematic research, experimentation, and collaboration.
- 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 10, 2026, 11:50 a.m.