Triple
T27749931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OpenCL 2.0 |
E702089
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | parallel programming framework specification |
C51168
|
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 programming framework specification Context triple: [OpenCL 2.0, instanceOf, parallel programming framework specification]
-
A.
parallel programming library
A parallel programming library is a collection of tools, abstractions, and APIs that enable developers to write programs that execute multiple computations concurrently across multiple cores, processors, or machines to improve performance and scalability.
-
B.
parallel computing standard
chosen
A parallel computing standard is a formally defined specification that enables coordinated execution and communication among multiple processing elements to efficiently perform computations concurrently across diverse hardware platforms.
-
C.
heterogeneous computing API specification
A heterogeneous computing API specification defines a standardized interface and behavior for coordinating and executing workloads across diverse processing units (such as CPUs, GPUs, and accelerators) within a unified programming model.
-
D.
parallel runtime scheduling algorithm
A parallel runtime scheduling algorithm is a strategy used by a runtime system to dynamically assign and balance tasks across multiple processing units to maximize concurrency, resource utilization, and overall performance.
-
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.
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_69ef6a53c7388190899baa6daf42301c |
completed | April 27, 2026, 1:53 p.m. |
Created at: April 27, 2026, 4:19 p.m.