Triple

T27762310
Position Surface form Disambiguated ID Type / Status
Subject Batch Normalization E701500 entity
Predicate instanceOf P0 FINISHED
Object deep learning technique C23071 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: deep learning technique
Context triple: [Batch Normalization, instanceOf, deep learning technique]
  • A. deep learning model
    A deep learning model is a computational architecture composed of multiple layers of interconnected processing units (neurons) that automatically learn hierarchical representations from data to perform tasks such as classification, prediction, or generation.
  • B. deep learning framework
    A deep learning framework is a software library or platform that provides tools, abstractions, and optimized components to design, train, and deploy neural network models efficiently.
  • C. deep learning library
    A deep learning library is a software framework that provides tools, abstractions, and optimized routines to design, train, and deploy neural network models.
  • D. machine learning paradigm
    A machine learning paradigm is a conceptual framework that defines how models learn from data, including the assumptions, learning objectives, and training procedures that guide the development and application of algorithms.
  • E. neural network normalization technique chosen
    A neural network normalization technique is a method that rescales and shifts activations or inputs within a model to stabilize training, improve convergence, and enhance generalization.
  • F. None of above.

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_69ef6a5193808190816eb7d0020b2d87 completed April 27, 2026, 1:53 p.m.
Created at: April 27, 2026, 4:28 p.m.