Triple

T4277531
Position Surface form Disambiguated ID Type / Status
Subject TF-Agents E97077 entity
Predicate supportsEnvironment P11908 FINISHED
Object MuJoCo environments
MuJoCo environments are physics-based continuous control simulation tasks widely used in reinforcement learning research and benchmarking.
 E426682 NE FINISHED

How this triple was built (4 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: MuJoCo environments | Statement: [TF-Agents, supportsEnvironment, MuJoCo environments]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MuJoCo environments
Context triple: [TF-Agents, supportsEnvironment, MuJoCo environments]
  • A. OpenAI Gym
    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. 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.
  • D. 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.
  • E. Stable Baselines
    Stable Baselines is a popular Python library that provides reliable, well-tested implementations of reinforcement learning algorithms built on top of OpenAI Baselines.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: MuJoCo environments
Triple: [TF-Agents, supportsEnvironment, MuJoCo environments]
Generated description
MuJoCo environments are physics-based continuous control simulation tasks widely used in reinforcement learning research and benchmarking.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MuJoCo environments
Target entity description: MuJoCo environments are physics-based continuous control simulation tasks widely used in reinforcement learning research and benchmarking.
  • A. OpenAI Gym
    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. 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.
  • D. 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.
  • E. Stable Baselines
    Stable Baselines is a popular Python library that provides reliable, well-tested implementations of reinforcement learning algorithms built on top of OpenAI Baselines.
  • F. None of above. chosen

Provenance (5 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_69b34544be3c819084d1ab82d29f90c5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3501ef1388190b0c968b069014a59 completed March 12, 2026, 11:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7b3b52c8190ae7c05448faf5558 completed March 14, 2026, 7:32 p.m.
NEDg Description generation batch_69b5b95083088190b0c993fa2fbc954c completed March 14, 2026, 7:38 p.m.
NED2 Entity disambiguation (via description) batch_69b5b9b8afcc8190822cfd560d064590 completed March 14, 2026, 7:40 p.m.
Created at: March 12, 2026, 11:07 p.m.