Triple

T12604969
Position Surface form Disambiguated ID Type / Status
Subject Network E300953 entity
Predicate cinematographyBy P1953 FINISHED
Object Owen Roizman E243100 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: Owen Roizman | Statement: [Network, cinematographyBy, Owen Roizman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Owen Roizman
Context triple: [Network, cinematographyBy, Owen Roizman]
  • A. Owen Roizman chosen
    Owen Roizman was an acclaimed American cinematographer known for his influential work on landmark films of the 1970s and beyond.
  • B. Lawrence Dobkin
    Lawrence Dobkin was an American character actor, director, and narrator known for his prolific work in film, television, and radio from the 1940s through the 1980s.
  • C. Jay Roach
    Jay Roach is an American film director and producer best known for helming hit comedies such as the Austin Powers series and Meet the Parents, as well as politically themed dramas like Recount and Trumbo.
  • D. David W. Zucker
    David W. Zucker is a television producer known for overseeing high-profile, prestige drama series, including the adaptation of Philip K. Dick’s "The Man in the High Castle."
  • E. Jeremy Leven
    Jeremy Leven is an American screenwriter, director, and novelist known for adapting romantic and character-driven stories for film, including the hit movie "The Notebook."
  • 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954e7f2dc8190a42cab7a0e5ea7f3 completed April 10, 2026, 7:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ecd1b748190bd961497b30e1ae5 completed May 2, 2026, 8:30 p.m.
Created at: April 9, 2026, 5:10 p.m.