Triple

T22202177
Position Surface form Disambiguated ID Type / Status
Subject parallel distributed processing E548708 entity
Predicate instanceOf P0 FINISHED
Object neural network model family 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 model family
Context triple: [parallel distributed processing, instanceOf, neural network model family]
  • A. large language model family
    A large language model family is a group of related neural network models that share a common architecture and training paradigm but vary in size, capabilities, and specialization to handle diverse natural language understanding and generation tasks.
  • B. 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.
  • 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 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.
  • E. 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.
  • 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_69e11e3ecc7c8190b5f94cd8f42e9d37 completed April 16, 2026, 5:37 p.m.
Created at: April 16, 2026, 8:36 p.m.