Triple

T18204182
Position Surface form Disambiguated ID Type / Status
Subject GPT-Neo E435863 entity
Predicate instanceOf P0 FINISHED
Object open-source language model C16400 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: open-source language model
Context triple: [GPT-Neo, instanceOf, open-source language model]
  • A. multimodal large language model family
    A multimodal large language model family is a group of related neural models that can jointly process and generate multiple data modalities—such as text, images, audio, or video—using shared architectures, training objectives, and parameterizations.
  • B. natural language processing model
    A natural language processing model is a computational system designed to understand, interpret, generate, and manipulate human language in a meaningful way.
  • C. large language model family chosen
    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.
  • D. large-scale model
    A large-scale model is a computational model, often in machine learning or simulation, that operates with vast numbers of parameters or variables to capture complex patterns or behaviors across extensive datasets or systems.
  • E. natural language understanding platform
    A natural language understanding platform is a system that interprets, analyzes, and derives meaning from human language input to enable intelligent, context-aware interactions and automation.
  • 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_69d8b90dba6481908e119eb9aa4ca0cb completed April 10, 2026, 8:47 a.m.
Created at: April 10, 2026, 10:32 a.m.