Triple

T805157
Position Surface form Disambiguated ID Type / Status
Subject OpenAI Gym E17413 entity
Predicate influenced P9 FINISHED
Object RLlib
RLlib is a scalable, open-source reinforcement learning library built on Ray that provides high-level APIs and distributed training support for a wide range of RL algorithms.
 E95190 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: RLlib | Statement: [OpenAI Gym, influenced, RLlib]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RLlib
Context triple: [OpenAI Gym, influenced, RLlib]
  • A. OpenAI Baselines
    OpenAI Baselines is a collection of high-quality reference implementations of reinforcement learning algorithms released by OpenAI for research and benchmarking.
  • B. OpenAI Gym
    OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms through a standardized collection of environments and interfaces.
  • C. TensorFlow
    TensorFlow is an open-source, end-to-end machine learning and deep learning framework widely used for building, training, and deploying neural network models at scale.
  • D. MuZero
    MuZero is a DeepMind reinforcement learning algorithm that learns to plan and master complex games like Go, chess, and Atari without being given the rules in advance.
  • E. Element AI
    Element AI was a Montreal-based artificial intelligence company and research lab known for developing enterprise AI solutions and advancing deep learning research.
  • 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: RLlib
Triple: [OpenAI Gym, influenced, RLlib]
Generated description
RLlib is a scalable, open-source reinforcement learning library built on Ray that provides high-level APIs and distributed training support for a wide range of RL algorithms.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RLlib
Target entity description: RLlib is a scalable, open-source reinforcement learning library built on Ray that provides high-level APIs and distributed training support for a wide range of RL algorithms.
  • A. OpenAI Baselines
    OpenAI Baselines is a collection of high-quality reference implementations of reinforcement learning algorithms released by OpenAI for research and benchmarking.
  • B. OpenAI Gym
    OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms through a standardized collection of environments and interfaces.
  • C. TensorFlow
    TensorFlow is an open-source, end-to-end machine learning and deep learning framework widely used for building, training, and deploying neural network models at scale.
  • D. MuZero
    MuZero is a DeepMind reinforcement learning algorithm that learns to plan and master complex games like Go, chess, and Atari without being given the rules in advance.
  • E. Element AI
    Element AI was a Montreal-based artificial intelligence company and research lab known for developing enterprise AI solutions and advancing deep learning research.
  • 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_69a4937ae8a08190b5084a03d532b30e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4aabff3d88190bec4299fa0d87df0 completed March 1, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69a68926c04081908923a7d114d1842d completed March 3, 2026, 7:09 a.m.
NEDg Description generation batch_69a693cf5f348190868cdf3539274aeb completed March 3, 2026, 7:54 a.m.
NED2 Entity disambiguation (via description) batch_69a6d5bc74008190b94ef7ea63f39671 completed March 3, 2026, 12:36 p.m.
Created at: March 1, 2026, 7:38 p.m.