Triple
T824089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OpenAI Baselines |
E17813
|
entity |
| Predicate | implementsAlgorithm |
P8649
|
FINISHED |
| Object |
PPO
PPO (Proximal Policy Optimization) is a popular reinforcement learning algorithm known for its stability and sample efficiency in training complex policies, especially in continuous control and high-dimensional environments.
|
E98478
|
NE FINISHED |
Provenance (5 batches)
| Stage | Batch ID | Job type | Status |
|---|---|---|---|
| creating | batch_69a4937c9c188190aaa216f6b466f452 |
elicitation | completed |
| NER | batch_69a4b2b503d48190bd4f33548a22d5fe |
ner | completed |
| NED1 | batch_69a76d93af548190818c14a370e0914a |
ned_source_triple | completed |
| NED2 | batch_69a7860e656c8190a08a9999662ba1f1 |
ned_description | completed |
| NEDg | batch_69a781f5536c81908175d58b6b75adba |
nedg | completed |
Created at: March 1, 2026, 7:38 p.m.