Triple
T18704966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ExampleValidator |
E457345
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | machine learning pipeline component |
C15636
|
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: machine learning pipeline component Context triple: [ExampleValidator, instanceOf, machine learning pipeline component]
-
A.
machine learning platform component
chosen
A machine learning platform component is a modular software element that provides specific functionality—such as data processing, model training, deployment, or monitoring—within an integrated ML lifecycle system.
-
B.
scikit-learn transformer
A scikit-learn transformer is an object that implements fit and transform methods to learn from training data and apply deterministic data transformations within machine learning pipelines.
-
C.
machine learning library
A machine learning library is a collection of tools, algorithms, and interfaces that simplifies building, training, evaluating, and deploying machine learning models.
-
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 engineer
A machine learning engineer designs, builds, and deploys data-driven models and systems that learn from data to make predictions or decisions at scale.
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 10, 2026, 11:49 a.m.