Triple
T17521235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MuJoCo environments |
E426682
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | physics-based simulation environment |
C23124
|
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: physics-based simulation environment Context triple: [MuJoCo environments, instanceOf, physics-based simulation environment]
-
A.
physics-based game
A physics-based game is an interactive digital experience where gameplay mechanics and outcomes are primarily driven by realistic or stylized simulation of physical laws such as gravity, momentum, and collision.
-
B.
physics engine
chosen
A physics engine is a software component that simulates physical systems—such as motion, collisions, and forces—in a virtual environment according to the laws of physics.
-
C.
virtual reality environment
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.
-
D.
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.
-
E.
research simulator
A research simulator is a virtual environment or tool that models real-world research processes, allowing users to design, conduct, and analyze simulated studies for learning, experimentation, or decision-making.
- 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
Created at: April 10, 2026, 5:49 a.m.