Triple

T9907960
Position Surface form Disambiguated ID Type / Status
Subject Guilty Conscience E185062 entity
Predicate usesVocalEffect P9331 FINISHED
Object Auto-Tune E294869 NE 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: [Guilty Conscience, usesVocalEffect, Auto-Tune]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Auto-Tune
Context triple: [Guilty Conscience, usesVocalEffect, Auto-Tune]
  • A. Auto-Tune chosen
    Auto-Tune is an audio processing technology that automatically corrects or stylizes vocal pitch, widely used in music production for both subtle tuning and distinctive robotic effects.
  • B. Audition
    "Audition (The Fools Who Dream)" is a pivotal, emotionally charged song from the film La La Land, performed by Emma Stone’s character as she reflects on the value of dreamers and artistic ambition.
  • C. Harmonizer
    Harmonizer is a 2021 studio album by American garage rock musician Ty Segall, noted for its heavier, synth-laced sound and experimental production.
  • D. Audion
    Audion is an early triode vacuum tube invented by Lee de Forest that enabled the amplification of electrical signals and was crucial to the development of radio and electronics.
  • E. DAW
    DAW was a United Nations division focused on promoting gender equality and advancing the status and rights of women worldwide.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca8296165881908ca4750701af1f29 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb50ec61481908f42bd2aa55d9a6e completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20daabd5881908b02da50a640766a completed April 5, 2026, 7:22 a.m.
Created at: March 30, 2026, 8:41 p.m.