Triple
T4276998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GridSearchCV |
E97067
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | model selection utility |
C15490
|
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: model selection utility Context triple: [GridSearchCV, instanceOf, model selection utility]
-
A.
former model
A former model is an individual who previously worked professionally in modeling but has since left the industry or no longer does it as their primary occupation.
-
B.
scientific model collection
A scientific model collection is an organized set of related theoretical, computational, or empirical models curated to represent, compare, and analyze phenomena within a specific scientific domain.
-
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.
criterion in numerical analysis
A criterion in numerical analysis is a quantitative condition or rule—such as a tolerance, convergence test, or stopping condition—used to assess the accuracy, stability, or termination of an algorithm or computational method.
-
E.
license selection tool
A license selection tool is a system that guides users through choosing an appropriate software or content license based on their project characteristics, distribution goals, and legal preferences.
- F. None of above. chosen
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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
Created at: March 12, 2026, 11:07 p.m.