Triple
T18300618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AEC API |
E438348
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | agent-environment cycle API |
C40128
|
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: agent-environment cycle API Context triple: [AEC API, instanceOf, agent-environment cycle API]
-
A.
reinforcement learning environment collection
A reinforcement learning environment collection is an organized set of diverse, standardized simulation or task environments designed to train, evaluate, and benchmark reinforcement learning agents.
-
B.
assistant
An assistant is an entity designed to support and facilitate a user's tasks or goals by providing information, guidance, and actions in response to their requests.
-
C.
space-time agent
A space-time agent is an autonomous entity capable of perceiving, reasoning about, and acting within both spatial and temporal dimensions to influence events and configurations across time.
-
D.
reinforcement learning library
A reinforcement learning library is a software toolkit that provides algorithms, environments, and utilities to design, train, evaluate, and deploy agents that learn optimal behaviors through trial-and-error interactions with their environment.
-
E.
graphical programming environment
A graphical programming environment is a software system that allows users to create, modify, and connect program elements visually (often via drag-and-drop blocks or diagrams) instead of writing traditional text-based code.
- 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
Created at: April 10, 2026, 10:35 a.m.