Triple
T11550833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warnock algorithm |
E273884
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | hidden surface determination algorithm |
C30224
|
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: hidden surface determination algorithm Context triple: [Warnock algorithm, instanceOf, hidden surface determination algorithm]
-
A.
computer graphics division
The computer graphics division is an organizational unit responsible for researching, developing, and producing visual content and technologies related to computer-generated imagery, animation, and interactive graphics.
-
B.
3D scene description framework
A 3D scene description framework is a structured system for representing, organizing, and exchanging information about objects, materials, lighting, and spatial relationships within a three-dimensional environment.
-
C.
opacity calculation project
An opacity calculation project is a computational initiative focused on modeling and quantifying how materials absorb, emit, and transmit radiation under varying physical conditions.
-
D.
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.
-
E.
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.
- 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_69d6aae4dfa48190a3ab0b19a159a3c5 |
completed | April 8, 2026, 7:22 p.m. |
Created at: April 8, 2026, 9:37 p.m.