Triple

T34139519
Position Surface form Disambiguated ID Type / Status
Subject Back to the Topic (Freestyle) E875671 entity
Predicate usesBeatType P179371 FINISHED
Object repurposed beat 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: repurposed beat | Statement: [Back to the Topic (Freestyle), usesBeatType, repurposed beat]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesBeatType
Context triple: [Back to the Topic (Freestyle), usesBeatType, repurposed beat]
  • A. usesBeatFrom
    Indicates that one entity employs or incorporates the rhythmic pattern, instrumental backing, or beat originally created for or associated with another entity.
  • B. hasDrivingBeat
    Indicates that something (typically a piece of music) features a strong, steady, and rhythmically propulsive beat that drives its momentum.
  • C. hasBeat
    Indicates that one entity has defeated or surpassed another in a competitive or comparative context.
  • D. hasElectronicBeat
    Indicates that the associated music or audio features a rhythm or backing track produced using electronic instruments or digital sound processing.
  • E. hasNotableBeat
    Indicates that an entity (such as a journalist or reporter) is professionally assigned to cover a specific topic, area, or subject as their primary reporting focus.
  • F. None of above. chosen

Provenance (4 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_69f349aaeef08190a20e72a3fdeb7052 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f720cc1bfc8190a16118e3af8e9316 completed May 3, 2026, 10:17 a.m.
PD Predicate disambiguation batch_69f71cc6397881909aaad37a9daa8a7e completed May 3, 2026, 10 a.m.
PDg Predicate description generation batch_69f71fb0172c81908f23e95ff16b0dec completed May 3, 2026, 10:13 a.m.
Created at: May 1, 2026, 1:53 a.m.