Triple

T21117095
Position Surface form Disambiguated ID Type / Status
Subject CBGB (film) E520326 entity
Predicate cinematographyBy P1953 FINISHED
Object Michael J. Ozier NE NERFINISHED

How this triple was built (3 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: Michael J. Ozier | Statement: [CBGB (film), cinematographyBy, Michael J. Ozier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael J. Ozier
Context triple: [CBGB (film), cinematographyBy, Michael J. Ozier]
  • A. Daniel M. Ziegler
    Daniel M. Ziegler is a researcher known for co-authoring influential work in artificial intelligence and machine learning, including large language model research.
  • B. Michael E. Bakich
    Michael E. Bakich is an American astronomy writer, editor, and popularizer of observational astronomy, long associated with Astronomy magazine.
  • C. Michael A. Helfant
    Michael A. Helfant is a film producer and entertainment executive known for his work on genre and thriller projects, including the 2013 crime thriller "The Call."
  • D. Michael Kozoll
    Michael Kozoll is an American television writer and producer best known for co-creating the influential police drama series "Hill Street Blues."
  • E. Max E. Youngstein
    Max E. Youngstein was an American film producer and studio executive known for his influential role at United Artists and for producing notable Cold War-era films.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Michael J. Ozier
Target entity description: Michael J. Ozier is a cinematographer best known for his work on the film "CBGB," which chronicles the iconic New York punk rock club.
  • A. Daniel M. Ziegler
    Daniel M. Ziegler is a researcher known for co-authoring influential work in artificial intelligence and machine learning, including large language model research.
  • B. Michael E. Bakich
    Michael E. Bakich is an American astronomy writer, editor, and popularizer of observational astronomy, long associated with Astronomy magazine.
  • C. Michael A. Helfant
    Michael A. Helfant is a film producer and entertainment executive known for his work on genre and thriller projects, including the 2013 crime thriller "The Call."
  • D. Michael Kozoll
    Michael Kozoll is an American television writer and producer best known for co-creating the influential police drama series "Hill Street Blues."
  • E. Max E. Youngstein
    Max E. Youngstein was an American film producer and studio executive known for his influential role at United Artists and for producing notable Cold War-era films.
  • F. None of above. chosen

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_69e0b50a623881909c0bbaf4f2c055e7 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e72106a3b48190a0efa51a74ae21f0 completed April 21, 2026, 7:02 a.m.
Created at: April 16, 2026, 2:55 p.m.