Triple

T18204378
Position Surface form Disambiguated ID Type / Status
Subject T5 E435867 entity
Predicate instanceOf P0 FINISHED
Object neural 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: neural language model
Context triple: [T5, instanceOf, neural language model]
  • A. 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.
  • 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. 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.
  • D. 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.
  • E. 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.
  • 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.