Triple

T18574939
Position Surface form Disambiguated ID Type / Status
Subject My Country, My Country E453960 entity
Predicate distributor P1951 FINISHED
Object Zeitgeist 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: Zeitgeist Films | Statement: [My Country, My Country, distributor, Zeitgeist Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zeitgeist Films
Context triple: [My Country, My Country, distributor, Zeitgeist Films]
  • A. Zeitgeist Films chosen
    Zeitgeist Films is an American independent film distribution company known for releasing art-house, foreign, and documentary films.
  • B. Kestrel Films
    Kestrel Films is a British film production company best known for producing Ken Loach’s acclaimed 1969 drama "Kes."
  • C. ThinkFilm
    ThinkFilm was an independent film distribution company known for releasing arthouse and specialty films in the early 2000s.
  • D. Katalyst Films
    Katalyst Films is a production company co-founded by Ashton Kutcher, best known for creating and producing popular prank and reality television shows and digital media content.
  • E. Revolution Films
    Revolution Films is a British film and television production company known for collaborating on acclaimed dramas and independent features, often with director Michael Winterbottom.
  • 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_69d8d38974308190a9174430ef256b73 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e543c8c0608190afc99235006bf87f completed April 19, 2026, 9:06 p.m.
Created at: April 10, 2026, 11:43 a.m.