Triple

T21499783
Position Surface form Disambiguated ID Type / Status
Subject SPEAKING model of speech events E530445 entity
Predicate instanceOf P0 FINISHED
Object model of speech events C39888 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: model of speech events
Context triple: [SPEAKING model of speech events, instanceOf, model of speech events]
  • A. automatic speech recognition system
    An automatic speech recognition system converts spoken language into written text by analyzing and interpreting audio signals using acoustic, linguistic, and statistical models.
  • B. speech foundation model
    A speech foundation model is a large-scale, pre-trained neural network designed to understand, generate, and transform spoken language across diverse tasks, languages, and acoustic conditions.
  • C. self-supervised speech representation learning model chosen
    A self-supervised speech representation learning model is a neural network that learns meaningful audio and speech feature representations directly from large amounts of unlabeled speech data by solving pretext tasks such as masked prediction or contrastive learning.
  • D. text-to-speech model
    A text-to-speech model is a system that converts written text into natural-sounding spoken audio using linguistic analysis and speech synthesis techniques.
  • E. speech codec
    A speech codec is a system that encodes and compresses spoken audio into a digital format for efficient transmission or storage and then decodes it back into intelligible speech.
  • 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_69e0c45bd15481909fba5910765cdda2 completed April 16, 2026, 11:13 a.m.
Created at: April 16, 2026, 6:24 p.m.