Triple

T18300778
Position Surface form Disambiguated ID Type / Status
Subject Farama Foundation E438351 entity
Predicate product P490 FINISHED
Object JaxMARL — NE NERFINISHED

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: JaxMARL | Statement: [Farama Foundation, product, JaxMARL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: JaxMARL
Context triple: [Farama Foundation, product, JaxMARL]
  • A. MPE (Multi-Agent Particle Environments)
    MPE (Multi-Agent Particle Environments) is a classic collection of lightweight 2D multi-agent reinforcement learning benchmark environments featuring simple particle-based agents and tasks like cooperation, competition, and communication.
  • B. Farama Foundation
    The Farama Foundation is an organization that develops and maintains open-source reinforcement learning tools and libraries for the research and engineering community.
  • C. 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.
  • D. ChainerRL
    ChainerRL is a reinforcement learning library built on top of the Chainer deep learning framework, providing tools and algorithms for training and evaluating RL agents.
  • E. 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.
  • 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: JaxMARL
Target entity description: JaxMARL is an open-source multi-agent reinforcement learning library built on JAX, designed to provide scalable, high-performance environments and tools for MARL research.
  • A. MPE (Multi-Agent Particle Environments)
    MPE (Multi-Agent Particle Environments) is a classic collection of lightweight 2D multi-agent reinforcement learning benchmark environments featuring simple particle-based agents and tasks like cooperation, competition, and communication.
  • B. Farama Foundation
    The Farama Foundation is an organization that develops and maintains open-source reinforcement learning tools and libraries for the research and engineering community.
  • C. 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.
  • D. ChainerRL
    ChainerRL is a reinforcement learning library built on top of the Chainer deep learning framework, providing tools and algorithms for training and evaluating RL agents.
  • E. 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.
  • F. None of above. chosen

Provenance (2 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_69d8b915e3e881909125d760c15d0c29 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e5017f63dc819083a675d570620f2f completed April 19, 2026, 4:23 p.m.
Created at: April 10, 2026, 10:35 a.m.