Triple
T38309223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AMD CDNA |
E1033639
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | data center 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: data center GPU architecture Context triple: [AMD CDNA, instanceOf, data center GPU architecture]
-
A.
data center GPU
A data center GPU is a high-performance graphics processing unit designed for server environments to accelerate large-scale parallel workloads such as AI, HPC, and data analytics with optimized power, cooling, and reliability features.
-
B.
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.
-
C.
data center network
A data center network is a specialized, high-performance communication infrastructure that interconnects servers, storage systems, and networking devices within and between data centers to enable efficient, reliable data exchange and application delivery.
-
D.
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.
-
E.
data center
A data center is a specialized facility that houses networked computer systems, storage, and infrastructure to process, manage, and store large volumes of digital data.
- 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_69f76e132c408190969b3d35c04b87ae |
completed | May 3, 2026, 3:47 p.m. |
Created at: May 3, 2026, 4:30 p.m.