Triple
T36642000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EdgeX Foundry |
E904608
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | edge computing framework |
C62707
|
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: edge computing framework Context triple: [EdgeX Foundry, instanceOf, edge computing framework]
-
A.
edge AI platform
An edge AI platform is an integrated hardware and software environment that deploys, manages, and runs artificial intelligence models directly on edge devices close to data sources, enabling low-latency, secure, and efficient processing without relying heavily on centralized cloud resources.
-
B.
engineering framework
An engineering framework is a structured set of principles, methods, and tools that guides the systematic design, development, and evaluation of engineering solutions.
-
C.
artificial intelligence framework
An artificial intelligence framework is a structured software environment that provides tools, libraries, and interfaces to design, train, deploy, and manage AI and machine learning models efficiently.
-
D.
deep learning framework
A deep learning framework is a software library or platform that provides tools, abstractions, and optimized components to design, train, and deploy neural network models efficiently.
-
E.
GPU computing framework
A GPU computing framework is a software platform that enables developers to write, manage, and optimize parallel programs that execute on graphics processing units for high-performance computation.
- 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_69f76e6c63e48190b1d0c3a79a6c7406 |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:11 p.m.