Triple
T14420918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nvidia Maxwell |
E357580
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | Nvidia GPU architecture |
C6593
|
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: Nvidia GPU architecture Context triple: [Nvidia Maxwell, instanceOf, Nvidia GPU architecture]
-
A.
GPU architecture
chosen
GPU architecture is the conceptual design and organization of a graphics processing unit’s cores, memory hierarchy, and data paths that enable massively parallel computation for graphics and general-purpose workloads.
-
B.
NVIDIA technology
NVIDIA technology encompasses a range of advanced hardware and software solutions—most notably GPUs, AI platforms, and high-performance computing systems—designed to accelerate graphics, data processing, and machine learning workloads across industries.
-
C.
graphics processing unit
A graphics processing unit (GPU) is a specialized electronic circuit designed to rapidly perform parallel mathematical and geometric calculations to render images, videos, and visual effects for display.
-
D.
graphics processing unit family
A graphics processing unit family is a group of closely related GPU models that share a common architecture, feature set, and design lineage, typically released by a manufacturer as a coherent product line.
-
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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
Created at: April 10, 2026, 1:18 a.m.