Triple
T15313024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AI2-THOR |
E366086
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | simulation platform |
C3873
|
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: simulation platform Context triple: [AI2-THOR, instanceOf, simulation platform]
-
A.
simulation technology company
A simulation technology company develops advanced software and hardware systems that create realistic virtual models of real-world processes, environments, or products to support training, analysis, design, and decision-making.
-
B.
research simulator
chosen
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.
-
C.
simulation centre
A simulation centre is a specialized facility equipped with realistic environments, tools, and technologies to replicate real-world scenarios for training, education, research, and performance evaluation.
-
D.
simulation technique
A simulation technique is a systematic method for modeling and imitating the behavior of real or hypothetical systems over time to analyze their performance, predict outcomes, or support decision-making.
-
E.
virtualization platform
A virtualization platform is a software-based system that enables multiple virtual machines or environments to run concurrently on a single physical hardware infrastructure, sharing resources while remaining logically isolated.
- 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.