Triple
T8823341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CUDA Fortran |
E209956
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | parallel programming language extension |
C13241
|
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 language extension Context triple: [CUDA Fortran, instanceOf, parallel programming language extension]
-
A.
programming language extension
chosen
A programming language extension is an add-on or modification that enhances an existing language with new syntax, features, or capabilities without fundamentally changing its core semantics.
-
B.
SIMD instruction set extension
A SIMD instruction set extension is a set of processor instructions that enable performing the same operation simultaneously on multiple data elements to accelerate parallelizable computations.
-
C.
programming language implementation
A programming language implementation is the concrete realization of a language’s specification, including its compiler or interpreter, runtime system, and associated tools that translate and execute programs written in that language.
-
D.
GPU-accelerated array library
A GPU-accelerated array library is a software toolkit that provides high-level, NumPy-like array operations executed on graphics processing units to enable massively parallel, high-performance numerical computing.
-
E.
programming language design
Programming language design is the process of defining the syntax, semantics, and features of a language to enable humans to express computations clearly, safely, and efficiently for execution by machines.
- 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_69ca8364e13081909c85fe80f44fe86f |
completed | March 30, 2026, 2:06 p.m. |
Created at: March 30, 2026, 6:46 p.m.