Triple

T1793154
Position Surface form Disambiguated ID Type / Status
Subject Atari deep Q-network E39543 entity
Predicate instanceOf P0 FINISHED
Object value-based reinforcement learning method C9067 CONCEPT FINISHED

How this triple was built (1 step)

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.

CD Concept disambiguation gpt-5-mini-2025-08-07 
Target class: value-based reinforcement learning method
Context triple: [Atari deep Q-network, instanceOf, value-based reinforcement learning method]
  • A. reinforcement learning library
    A reinforcement learning library is a software toolkit that provides algorithms, environments, and utilities to design, train, evaluate, and deploy agents that learn optimal behaviors through trial-and-error interactions with their environment.
  • B. behaviorist
    A behaviorist is a psychologist or theorist who explains learning and behavior primarily in terms of observable actions and environmental stimuli, rather than internal mental states.
  • C. value resort
    A value resort is a budget-friendly vacation property that offers essential amenities and comfortable accommodations at lower prices than traditional resorts, often with fewer luxury features but convenient access to key attractions.
  • D. valet
    A valet is a service worker responsible for courteously parking, retrieving, and sometimes safeguarding guests’ vehicles, often at hotels, restaurants, or events.
  • E. behavioral psychology tool
    A behavioral psychology tool is an instrument, method, or software designed to observe, measure, and modify human behavior by applying principles of learning and motivation.
  • F. None of above. chosen

Provenance (1 batch)

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_69a88631854081909723959921e45c2b completed March 4, 2026, 7:21 p.m.
Created at: March 4, 2026, 7:32 p.m.