Triple

T5577315
Position Surface form Disambiguated ID Type / Status
Subject Glitter (album) E146350 entity
Predicate basedOn P98 FINISHED
Object Glitter (film) E26323 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: Glitter (film) | Statement: [Glitter (album), basedOn, Glitter (film)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Glitter (film)
Context triple: [Glitter (album), basedOn, Glitter (film)]
  • A. Glitter
    "Glitter" is an introspective, genre-blending EP by 070 Shake that helped establish her as a distinctive voice in contemporary hip-hop and alternative R&B.
  • B. Glitter
    Glitter is a 2001 musical romantic drama film starring Mariah Carey as an aspiring singer navigating love and the music industry in 1980s New York City.
  • C. Glitter (album)
    Glitter is the 2001 soundtrack album by Mariah Carey, blending pop, R&B, and disco influences and released alongside her film of the same name.
  • D. film "Glitter" chosen
    "Glitter" is a 2001 musical drama film starring Mariah Carey as an aspiring singer navigating love and the music industry in 1980s New York.
  • E. Glitz
    Glitz is a crime novel by Elmore Leonard that follows a tough Miami cop entangled with a vengeful ex-con and the seedy underworld of Atlantic City.
  • 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_69c008ffed108190a084602227af6157 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c0206ae4808190971d89243db94475 completed March 22, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c059f3f6648190af2fd9a5e7cc125b completed March 22, 2026, 9:07 p.m.
Created at: March 22, 2026, 3:37 p.m.