Triple
T1893360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NVIDIA CUDA |
E41922
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | parallel computing platform |
C5173
|
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: parallel computing platform Context triple: [NVIDIA CUDA, instanceOf, parallel computing platform]
-
A.
GPU computing framework
chosen
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.
-
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.
data center platform
A data center platform is an integrated environment of hardware, software, and management tools that provides scalable, secure, and reliable infrastructure for hosting, processing, and managing data and applications.
-
D.
virtualization platform
A virtualization platform is a software-based system that enables multiple virtual machines or environments to run concurrently on a single physical hardware infrastructure, sharing resources while remaining logically isolated.
-
E.
cross-platform development framework
A cross-platform development framework is a software toolkit that enables developers to build applications that run on multiple operating systems or devices from a single shared codebase.
- 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_69a8864b6de0819098d089f6a1b910a7 |
completed | March 4, 2026, 7:21 p.m. |
Created at: March 4, 2026, 7:34 p.m.