SuperSuit
E438352
SuperSuit is a companion library to the PettingZoo multi-agent reinforcement learning framework that provides a collection of preprocessing wrappers to transform and standardize environments for easier experimentation.
All labels observed (1)
| Label | Occurrences |
|---|---|
| SuperSuit canonical | 4 |
How this entity was disambiguated
This entity first appeared as the object of triple T4425230 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SuperSuit Context triple: [PettingZoo, relatedTo, SuperSuit]
-
A.
The Super
The Super is a 2017 American thriller film about a former cop who becomes the superintendent of a New York City apartment building where tenants begin mysteriously disappearing.
-
B.
Bootjack
Bootjack is a small unincorporated community located in Mariposa County, California, near the Sierra Nevada foothills and the gateway to Yosemite National Park.
-
C.
Super Sixth
Super Sixth is the nickname of the U.S. Army’s 6th Armored Division, a World War II armored unit noted for its rapid advances and key role in the European theater.
-
D.
Toys for Bob
Toys for Bob is an American video game developer best known for creating the Skylanders series and working on remakes like the Spyro Reignited Trilogy.
-
E.
Autoport
Autoport is a specialized automotive terminal within the Port of Boston used for handling, storing, and processing imported and exported vehicles.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SuperSuit Target entity description: SuperSuit is a companion library to the PettingZoo multi-agent reinforcement learning framework that provides a collection of preprocessing wrappers to transform and standardize environments for easier experimentation.
-
A.
The Super
The Super is a 2017 American thriller film about a former cop who becomes the superintendent of a New York City apartment building where tenants begin mysteriously disappearing.
-
B.
Bootjack
Bootjack is a small unincorporated community located in Mariposa County, California, near the Sierra Nevada foothills and the gateway to Yosemite National Park.
-
C.
Super Sixth
Super Sixth is the nickname of the U.S. Army’s 6th Armored Division, a World War II armored unit noted for its rapid advances and key role in the European theater.
-
D.
Toys for Bob
Toys for Bob is an American video game developer best known for creating the Skylanders series and working on remakes like the Spyro Reignited Trilogy.
-
E.
Autoport
Autoport is a specialized automotive terminal within the Port of Boston used for handling, storing, and processing imported and exported vehicles.
- F. None of above. chosen
Statements (30)
| Predicate | Object |
|---|---|
| instanceOf |
Python library
ⓘ
reinforcement learning tool ⓘ software library ⓘ |
| applicationArea |
multi-agent RL benchmarks
ⓘ
reinforcement learning research ⓘ |
| compatibleWith | PettingZoo ⓘ |
| domain | multi-agent reinforcement learning ⓘ |
| feature |
composable wrappers
ⓘ
environment transformation utilities ⓘ standardized wrappers API ⓘ |
| goal | to make multi-agent RL experimentation easier ⓘ |
| hostedOn | GitHub ⓘ |
| license | open-source software ⓘ |
| maintainedBy | PettingZoo developers ⓘ |
| name | SuperSuit ⓘ |
| partOfEcosystem | PettingZoo ecosystem ⓘ |
| programmingLanguage | Python ⓘ |
| provides | preprocessing wrappers ⓘ |
| purpose |
to facilitate experimentation in multi-agent reinforcement learning
ⓘ
to standardize multi-agent environments ⓘ to transform multi-agent environments ⓘ |
| relatedTo | PettingZoo ⓘ |
| supports |
PettingZoo environments
ⓘ
gym-style environments via PettingZoo wrappers ⓘ |
| targetUser |
multi-agent RL practitioners
ⓘ
reinforcement learning researchers ⓘ |
| useCase |
action space transformations
ⓘ
environment preprocessing ⓘ observation transformations ⓘ reward preprocessing ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: SuperSuit Description of subject: SuperSuit is a companion library to the PettingZoo multi-agent reinforcement learning framework that provides a collection of preprocessing wrappers to transform and standardize environments for easier experimentation.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.