Triple

T22103839
Position Surface form Disambiguated ID Type / Status
Subject Australia (2008 film) E546235 entity
Predicate productionCompany P490 FINISHED
Object Bazmark Films NE NERFINISHED

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: Bazmark Films | Statement: [Australia (2008 film), productionCompany, Bazmark Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bazmark Films
Context triple: [Australia (2008 film), productionCompany, Bazmark Films]
  • A. Bazmark Films chosen
    Bazmark Films is an Australian film production company founded by director Baz Luhrmann, known for producing his visually distinctive and stylized movies such as Moulin Rouge! and The Great Gatsby.
  • B. Rainmark Films
    Rainmark Films is a British film and television production company known for producing high-quality dramas and feature films.
  • C. BAC Films
    BAC Films is a French film distribution company known for handling a wide range of independent and international cinema releases.
  • D. Maddock Films
    Maddock Films is an Indian film production company known for backing popular Hindi movies across genres, including comedies, thrillers, and offbeat dramas.
  • E. Brio Films
    Brio Films is a French film production company known for producing imaginative and visually distinctive movies such as Michel Gondry’s "Mood Indigo."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e378dc08190896d6a51597afd5a completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129175a7881909549883f23c53dca completed April 28, 2026, 9:39 p.m.
Created at: April 16, 2026, 8:30 p.m.