Triple

T33266717
Position Surface form Disambiguated ID Type / Status
Subject Diva (Remix) E851667 entity
Predicate hasTempoRelationToOriginal P192379 FINISHED
Object similar or slightly modified from Diva 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: similar or slightly modified from Diva | Statement: [Diva (Remix), hasTempoRelationToOriginal, similar or slightly modified from Diva]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTempoRelationToOriginal
Context triple: [Diva (Remix), hasTempoRelationToOriginal, similar or slightly modified from Diva]
  • A. hasTempoRelativeToOriginal chosen
    Indicates that one entity’s tempo is defined or measured in relation to the tempo of an original reference version.
  • B. hasTempoChanges
    Indicates that the tempo of the piece or segment changes over its duration, rather than remaining constant.
  • C. hasTempoVariety
    Indicates that an entity exhibits variation or changes in tempo rather than maintaining a constant speed.
  • D. hasFamousVersionTempo
    Indicates that one entity is a tempo that characterizes a well-known or widely recognized version of another entity (such as a musical work or performance).
  • E. hasTempoOrientation
    Indicates that one entity is characterized by a particular temporal direction or alignment (such as past-, present-, or future-oriented) in relation to another entity or context.
  • 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_69f349642dac81908a37ffcc3b976a55 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69fd82ed2a4c81908bd7797fbd2e3d08 completed May 8, 2026, 6:30 a.m.
PD Predicate disambiguation batch_69fd814cc10481908e4f8123d35a5d0c completed May 8, 2026, 6:23 a.m.
Created at: May 1, 2026, 1:32 a.m.