Triple

T18300691
Position Surface form Disambiguated ID Type / Status
Subject Tianshou E438349 entity
Predicate supportsAlgorithm P203 FINISHED
Object A3C NE NERFINISHED

How this triple was built (2 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: A3C | Statement: [Tianshou, supportsAlgorithm, A3C]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: A3C
Context triple: [Tianshou, supportsAlgorithm, A3C]
  • A. A3C chosen
    A3C (Asynchronous Advantage Actor-Critic) is a reinforcement learning algorithm that trains multiple parallel agents to learn policies and value functions efficiently using asynchronous gradient updates.
  • B. A2C
    A2C (Advantage Actor-Critic) is a popular synchronous policy gradient reinforcement learning algorithm that combines value-based and policy-based methods to improve training stability and efficiency.
  • C. A-3
    The A-3 is a major Spanish motorway that connects Madrid with Valencia and the eastern Mediterranean coast.
  • D. A33
    A33 is a major road in southern England that runs between Reading and Southampton, serving as an important regional transport route.
  • E. AIC
    AIC is the collective term for Australia’s national intelligence agencies responsible for gathering, assessing, and disseminating security and foreign intelligence.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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.