Triple
T4293723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stable Baselines |
E99657
|
entity |
| Predicate | supportsEnvironmentInterface |
P11686
|
FINISHED |
| Object | OpenAI Gym |
E17413
|
NE FINISHED |
How this triple was built (3 steps)
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.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: OpenAI Gym | Statement: [Stable Baselines, supportsEnvironmentInterface, OpenAI Gym]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OpenAI Gym Context triple: [Stable Baselines, supportsEnvironmentInterface, OpenAI Gym]
-
A.
OpenAI Gym
chosen
OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms through a standardized collection of environments and interfaces.
-
B.
OpenAI Baselines
OpenAI Baselines is a collection of high-quality reference implementations of reinforcement learning algorithms released by OpenAI for research and benchmarking.
-
C.
MuJoCo environments
MuJoCo environments are physics-based continuous control simulation tasks widely used in reinforcement learning research and benchmarking.
-
D.
Arcade Learning Environment
Arcade Learning Environment is a widely used research platform that provides a suite of Atari 2600 games for developing and evaluating reinforcement learning algorithms.
-
E.
TF-Agents
TF-Agents is an open-source library built on TensorFlow that provides modular components and tools for developing, training, and evaluating reinforcement learning algorithms.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsEnvironmentInterface Context triple: [Stable Baselines, supportsEnvironmentInterface, OpenAI Gym]
-
A.
supportsEnvironment
Indicates that one entity provides the necessary conditions, compatibility, or resources for another entity to operate or exist within a particular environment.
-
B.
hasEnvironmentType
Indicates that an entity is associated with or occurs within a specific type or category of environment.
-
C.
supportsConfigurationFromEnv
Indicates that a component can obtain and apply its configuration settings directly from environment variables.
-
D.
usesInterface
chosen
Indicates that one entity interacts with or operates another entity through a specified interface or set of interface methods.
-
E.
supportsImplementationOf
Indicates that one entity provides the necessary resources, framework, or assistance for another entity to be carried out, realized, or put into practice.
- F. None of above.
Provenance (4 batches)
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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35082228081908504e3fd7c4ca1e8 |
completed | March 12, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c73d47448190a844bc13eae84a54 |
completed | March 14, 2026, 8:38 p.m. |
| PD | Predicate disambiguation | batch_69b347fe55a88190b77bab0c0f38e1aa |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:08 p.m.