Triple
T15313025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AI2-THOR |
E366086
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | 3D simulation environment |
C12698
|
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: 3D simulation environment Context triple: [AI2-THOR, instanceOf, 3D simulation environment]
-
A.
virtual reality environment
chosen
A virtual reality environment is a computer-generated, immersive 3D space that users can interact with in real time through specialized hardware and software, simulating presence in a digital world.
-
B.
space environment simulation laboratory
A space environment simulation laboratory is a controlled facility that recreates key physical conditions of outer space—such as vacuum, radiation, extreme temperatures, and microgravity—to test and study spacecraft components, materials, and biological systems.
-
C.
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.
-
D.
3D radar
A 3D radar is a sensing system that measures the range, direction, and elevation of targets to provide a three-dimensional representation of their position in space.
-
E.
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.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
Created at: April 10, 2026, 3:16 a.m.