Triple

T9744380
Position Surface form Disambiguated ID Type / Status
Subject peer instruction E236269 entity
Predicate instanceOf P0 FINISHED
Object active learning strategy C27203 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: active learning strategy
Context triple: [peer instruction, instanceOf, active learning strategy]
  • A. adaptive learning rate method
    An adaptive learning rate method is an optimization technique that automatically adjusts the step size for each parameter during training based on past gradient information to improve convergence speed and stability.
  • B. learning theory
    Learning theory is the conceptual framework that explains how knowledge and skills are acquired, processed, retained, and applied through experience, instruction, and practice.
  • C. activation function
    An activation function is a mathematical operation applied to a neuron's input in a neural network to introduce non-linearity and determine the neuron's output signal.
  • D. value-based reinforcement learning method
    A value-based reinforcement learning method is an approach that learns a value function estimating expected future rewards for states or state-action pairs and derives a policy by selecting actions that maximize these estimated values.
  • E. model-based reinforcement learning algorithm
    A model-based reinforcement learning algorithm is a decision-making method that learns or uses an explicit model of the environment’s dynamics to plan and select actions that maximize long-term rewards.
  • 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_69ca84d3e24481908a476e2231123cf9 completed March 30, 2026, 2:12 p.m.
Created at: March 30, 2026, 8:23 p.m.