Triple

T22202176
Position Surface form Disambiguated ID Type / Status
Subject parallel distributed processing E548708 entity
Predicate instanceOf P0 FINISHED
Object connectionist approach C39344 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: connectionist approach
Context triple: [parallel distributed processing, instanceOf, connectionist approach]
  • A. associative memory model
    An associative memory model is a computational or theoretical framework that stores and retrieves information based on learned relationships or patterns between items, enabling recall of one item when presented with another related cue.
  • B. symbolic cognitive architecture
    A symbolic cognitive architecture is a computational framework that models human-like cognition using explicit, manipulable symbols and rule-based processes to represent and transform knowledge.
  • C. machine learning paradigm chosen
    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.
  • D. neural networks conference
    A neural networks conference is a professional gathering where researchers, practitioners, and industry experts present, discuss, and collaborate on the latest advances, applications, and theories in neural network and deep learning technologies.
  • E. 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.
  • 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.