Triple
T16076461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AMD Instinct MI250X |
E389990
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | data center GPU |
C36935
|
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 Context triple: [AMD Instinct MI250X, instanceOf, data center GPU]
-
A.
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.
-
B.
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.
-
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.
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.
-
E.
data center infrastructure management platform
A data center infrastructure management platform is a centralized software system that monitors, analyzes, and optimizes the physical and virtual resources, power, cooling, and capacity of data centers to improve efficiency, reliability, and planning.
- F. None of above. chosen
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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
Created at: April 10, 2026, 4:57 a.m.