Triple
T38672122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ATI Mach series |
E943624
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | 2D graphics accelerator |
C63205
|
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: 2D graphics accelerator Context triple: [ATI Mach series, instanceOf, 2D graphics accelerator]
-
A.
graphics acceleration technology
Graphics acceleration technology is specialized hardware and software that offloads and speeds up the processing of visual and graphical computations, enabling smoother rendering and higher performance for images, videos, and 3D applications.
-
B.
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.
-
C.
2D graphics system
A 2D graphics system is a software or hardware framework that creates, manipulates, and renders two-dimensional visual elements such as shapes, text, and images on a display surface.
-
D.
computer graphics chipset family
A computer graphics chipset family is a group of closely related graphics processing chipsets that share a common architecture, feature set, and design lineage, tailored for rendering and accelerating visual output across different devices or performance tiers.
-
E.
hardware accelerator
A hardware accelerator is a specialized computing device or component designed to perform specific tasks or algorithms more efficiently and faster than a general-purpose processor.
- 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_69f76eec28708190b9c82a505fc278e0 |
completed | May 3, 2026, 3:51 p.m. |
Created at: May 3, 2026, 4:33 p.m.