Triple

T3542949
Position Surface form Disambiguated ID Type / Status
Subject ResNet E74928 entity
Predicate instanceOf P0 FINISHED
Object residual network 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: residual network
Context triple: [ResNet, instanceOf, residual network]
  • 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. recurrent artificial neural network
    A recurrent artificial neural network is a type of neural network where connections form directed cycles, allowing information to persist over time and enabling the modeling of sequential or temporal data.
  • C. 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.
  • D. 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.
  • E. image recognition model
    An image recognition model is a computational system that analyzes visual input to automatically identify, classify, and sometimes localize objects, patterns, or features within images.
  • 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_69ad85d274cc8190ab59c97298a1cfbf completed March 8, 2026, 2:21 p.m.
Created at: March 8, 2026, 3:20 p.m.