Triple

T3021148
Position Surface form Disambiguated ID Type / Status
Subject No Child Left Behind E82456 entity
Predicate featuresVocalEffects P9331 FINISHED
Object Auto-Tune LITERAL FINISHED

How this triple was built (2 steps)

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.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Auto-Tune | Statement: [No Child Left Behind, featuresVocalEffects, Auto-Tune]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: featuresVocalEffects
Context triple: [No Child Left Behind, featuresVocalEffects, Auto-Tune]
  • A. featuresVocalist
    Indicates that one entity (such as a song, track, or performance) includes another entity serving as a vocalist or featured singer.
  • B. vocalForces
    Indicates a relationship where one entity uses vocal expression (such as speech, singing, or sound) to exert influence, pressure, or compulsion on another entity.
  • C. vocalizationCharacteristic
    Indicates how an entity’s vocal sounds are characterized, such as their quality, style, or distinctive acoustic features.
  • D. audioModulation
    Indicates a relationship where one audio signal or parameter is used to vary or control another audio signal’s characteristics (such as amplitude, frequency, or timbre) over time.
  • E. vocalizationMethod chosen
    Indicates the manner or technique by which an entity produces a sound or vocal expression.
  • F. None of above.

Provenance (3 batches)

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_69ad8b1fb34081908c1b873e2b7273e1 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a951e688190b3e35909affd3bfd completed March 8, 2026, 3:49 p.m.
PD Predicate disambiguation batch_69ad961c430c8190ac48f2e3c7e7c649 completed March 8, 2026, 3:30 p.m.
Created at: March 8, 2026, 3 p.m.