Triple

T19328485
Position Surface form Disambiguated ID Type / Status
Subject Death Comes to Pemberley E483421 entity
Predicate productionCompany P490 FINISHED
Object Origin Pictures 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: Origin Pictures | Statement: [Death Comes to Pemberley, productionCompany, Origin Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Origin Pictures
Context triple: [Death Comes to Pemberley, productionCompany, Origin Pictures]
  • A. Origin Pictures chosen
    Origin Pictures is a British film and television production company known for producing high-quality literary adaptations and drama projects.
  • B. Impact Pictures
    Impact Pictures is a film production company best known for producing action and science-fiction movies, including entries in the Resident Evil franchise.
  • C. Imagine Films
    Imagine Films is a film production division associated with the American entertainment company Imagine Entertainment, known for developing and producing motion pictures.
  • D. Gigantic Pictures
    Gigantic Pictures is an independent film production company known for backing critically acclaimed, character-driven movies.
  • E. Citizen Pictures
    Citizen Pictures is a television production company best known for creating popular food and travel shows, including Guy Fieri’s long-running series "Diners, Drive-Ins and Dives."
  • 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_69d8e8d13e3c81909d91d1d5ec37c095 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e6163f32f48190be17cccf4e537372 completed April 20, 2026, 12:04 p.m.
Created at: April 10, 2026, 1:33 p.m.