Triple

T9830236
Position Surface form Disambiguated ID Type / Status
Subject Detroit (2017 film) E238763 entity
Predicate productionCompany P490 FINISHED
Object Annapurna Pictures E244440 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: Annapurna Pictures | Statement: [Detroit (2017 film), productionCompany, Annapurna Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Annapurna Pictures
Context triple: [Detroit (2017 film), productionCompany, Annapurna Pictures]
  • A. Annapurna Pictures chosen
    Annapurna Pictures is an American film production company known for backing critically acclaimed, auteur-driven movies such as "Her," "Zero Dark Thirty," and "American Hustle."
  • B. Everest Pictures
    Everest Pictures is a film production company known for producing the psychological drama "David and Lisa."
  • C. Benaroya Pictures
    Benaroya Pictures is an independent film production company known for financing and producing a range of critically acclaimed and commercially successful feature films.
  • D. Troika Pictures
    Troika Pictures is a film production company known for producing feature films such as the thriller "The Call" (2013).
  • E. Magnolia Pictures
    Magnolia Pictures is an American independent film distribution company known for releasing a wide range of arthouse, documentary, and foreign films.
  • 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_69ca84e0dd1881909800765d1e21f735 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3297bd88190bf8c53a4ba00e0ae completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc8ca2808190a1da0641162f12d1 completed April 5, 2026, 2:44 a.m.
Created at: March 30, 2026, 8:32 p.m.