Triple
T29867575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Material Definition Language |
E758497
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | physically based shading language |
C25478
|
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: physically based shading language Context triple: [Material Definition Language, instanceOf, physically based shading language]
-
A.
GPU programming language
chosen
A GPU programming language is a specialized language or extension designed to express highly parallel computations that run efficiently on graphics processing units.
-
B.
Khronos Group standard
A Khronos Group standard is an open, royalty-free specification developed collaboratively by the Khronos Group consortium to enable cross-platform, cross-vendor interoperability for graphics, compute, and media applications.
-
C.
3D rendering engine
A 3D rendering engine is a software component that transforms 3D scene data—geometry, materials, lighting, and camera parameters—into 2D images or frames through processes like rasterization or ray tracing.
-
D.
real-time rendering technology
Real-time rendering technology is a class of systems and algorithms that generate and display interactive, visually coherent images or scenes at high frame rates, typically for applications like games, simulations, and virtual reality.
-
E.
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.
- 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_69f2245b4dec8190b85f664d918a00a5 |
completed | April 29, 2026, 3:31 p.m. |
Created at: April 29, 2026, 5:52 p.m.