Triple

T37152462
Position Surface form Disambiguated ID Type / Status
Subject Sparks Fly E920395 entity
Predicate basedOnCareerTransition P88172 FINISHED
Object transition from television star to recording artist 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: transition from television star to recording artist | Statement: [Sparks Fly, basedOnCareerTransition, transition from television star to recording artist]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: basedOnCareerTransition
Context triple: [Sparks Fly, basedOnCareerTransition, transition from television star to recording artist]
  • A. basedOnCareerOf chosen
    Indicates that something (such as a work, character, or storyline) is derived from, inspired by, or modeled on the career or professional life of a particular person.
  • B. isCareerBased
    Indicates that something is determined, structured, or oriented around a person’s career or professional path.
  • C. basedOnProfession
    Indicates that the relationship or action is determined or derived from a person’s profession or occupational role.
  • D. managedCareerOf
    Indicates that one entity was responsible for overseeing, directing, or handling the professional career of another entity.
  • E. careerImpact
    Indicates how one entity influences or changes another entity’s professional trajectory, opportunities, or outcomes.
  • 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_69f76e9f87c08190b4c8f7fafbd8345a completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69ff5b233e9c8190adc06cca0758986b completed May 9, 2026, 4:04 p.m.
PD Predicate disambiguation batch_69ff5a5682108190a006b23c4fcdcc7c completed May 9, 2026, 4:01 p.m.
Created at: May 3, 2026, 4:15 p.m.