Triple

T15939385
Position Surface form Disambiguated ID Type / Status
Subject 0 to 100 / The Catch Up E386518 entity
Predicate hasChoppedAndScrewed P121063 FINISHED
Object frequently remixed by DJs 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: frequently remixed by DJs | Statement: [0 to 100 / The Catch Up, hasChoppedAndScrewed, frequently remixed by DJs]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasChoppedAndScrewed
Context triple: [0 to 100 / The Catch Up, hasChoppedAndScrewed, frequently remixed by DJs]
  • A. hasCut
    Indicates that one entity has made or possesses a cut in, on, or through another entity.
  • B. hasTypicalCut
    Indicates that one entity is characterized by or associated with a standard or typical type of cut of another entity.
  • C. isCutInto
    Indicates that one entity is divided or separated into pieces or segments that become the other entity.
  • D. hasChicane
    Indicates that one entity incorporates or features a chicane (a sharp, S-shaped bend or series of bends), typically in the context of a track, route, or path.
  • E. hasTwist
    Indicates that an entity (such as a story, object, or feature) includes an unexpected change, reversal, or surprising element relative to what was previously established or anticipated.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e17d4d08f481909f38b75e3f42d9ab completed April 17, 2026, 12:22 a.m.
PD Predicate disambiguation batch_69e142d37cd88190ab50760f1783e20c completed April 16, 2026, 8:13 p.m.
PDg Predicate description generation batch_69e17d48cc9c8190b03fd07ae2e9dfd8 completed April 17, 2026, 12:22 a.m.
Created at: April 10, 2026, 4:53 a.m.