Triple

T16968188
Position Surface form Disambiguated ID Type / Status
Subject Bullet Train (2022 film) E411596 entity
Predicate productionCompany P490 FINISHED
Object Fuqua Films E1013787 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: Fuqua Films | Statement: [Bullet Train (2022 film), productionCompany, Fuqua Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fuqua Films
Context triple: [Bullet Train (2022 film), productionCompany, Fuqua Films]
  • A. Fuqua Films chosen
    Fuqua Films is an American film and television production company founded by director Antoine Fuqua, known for producing action-driven and dramatic projects.
  • B. Vinson Films
    Vinson Films is a film production company known for producing the 2019 horror-comedy thriller "Ready or Not."
  • C. Rhea Films
    Rhea Films is a film production company known for collaborating on independent, critically acclaimed movies such as the crime thriller "Good Time."
  • D. Waverly Films
    Waverly Films is a Brooklyn-based film and video production collective known for its offbeat comedy shorts, music videos, and collaborations with major studios and brands.
  • E. Sunrise Films
    Sunrise Films is a film distribution company known for handling the release of independent and international movies such as "Dinner Rush."
  • 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_69d886c9c9d481909afe222093641cae completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d0a6f628819080db47285954729a completed April 18, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d46f1d608190befe4dcbda086c03 completed May 10, 2026, 6:54 p.m.
Created at: April 10, 2026, 5:31 a.m.