Triple

T36491624
Position Surface form Disambiguated ID Type / Status
Subject Prototypical Networks E899064 entity
Predicate instanceOf P0 FINISHED
Object neural network based model C4177 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: neural network based model
Context triple: [Prototypical Networks, instanceOf, neural network based model]
  • A. deep learning model chosen
    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. neural network component
    A neural network component is a modular unit—such as a layer, activation function, or connection pattern—that processes and transforms input data as part of a larger neural architecture to enable learning and inference.
  • C. neural network modeling language
    A neural network modeling language is a specialized formalism or syntax used to define, configure, and connect neural network components and architectures in a clear, structured, and often platform-agnostic way.
  • D. neural network design method
    A neural network design method is a systematic approach for selecting, structuring, and configuring neural network architectures and training procedures to solve specific computational or learning tasks.
  • E. neural network API
    A neural network API is an interface that allows developers to build, configure, train, and deploy neural network models programmatically without managing low-level implementation details.
  • 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_69f76e5ad4588190bdbce60c52fbb785 completed May 3, 2026, 3:48 p.m.
Created at: May 3, 2026, 4:10 p.m.