Triple

T8993040
Position Surface form Disambiguated ID Type / Status
Subject Elmo E214835 entity
Predicate instanceOf P0 FINISHED
Object deep contextualized word representation model 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: deep contextualized word representation model
Context triple: [Elmo, instanceOf, deep contextualized word representation 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 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.
  • C. 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.
  • D. 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.
  • E. 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.
  • 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_69ca83a05c608190bdfdbdb25e994b39 completed March 30, 2026, 2:07 p.m.
Created at: March 30, 2026, 7:04 p.m.