Triple
T7985002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azure Machine Learning |
E185664
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | cloud-based machine learning service |
C6083
|
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: cloud-based machine learning service Context triple: [Azure Machine Learning, instanceOf, cloud-based machine learning service]
-
A.
cloud service
chosen
A cloud service is an on-demand, internet-delivered computing resource—such as storage, processing power, or applications—managed by a provider and accessed remotely by users.
-
B.
cloud computing platform
A cloud computing platform is an integrated environment that provides on-demand access to scalable computing resources, storage, and services over the internet, enabling users to deploy, manage, and run applications without managing underlying hardware.
-
C.
machine learning platform component
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.
-
D.
cloud storage service
A cloud storage service is an online platform that securely stores, syncs, and manages users’ digital files on remote servers, enabling access and sharing from any internet-connected device.
-
E.
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.
- 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_69ca829a2cfc819083d591d58ec04075 |
completed | March 30, 2026, 2:03 p.m. |
Created at: March 30, 2026, 5:15 p.m.