Triple

T4063749
Position Surface form Disambiguated ID Type / Status
Subject 8MM E86275 entity
Predicate producer P490 FINISHED
Object Gail Katz E300014 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: Gail Katz | Statement: [8MM, producer, Gail Katz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gail Katz
Context triple: [8MM, producer, Gail Katz]
  • A. Gail Katz chosen
    Gail Katz is an American film and television producer known for working on major Hollywood projects including the disaster drama "The Perfect Storm."
  • B. Gloria Katz
    Gloria Katz was an American screenwriter and producer best known for her collaborations with George Lucas, including work on films like "American Graffiti" and "Star Wars."
  • C. Gail Berman
    Gail Berman is an American television and film producer and media executive known for her influential roles at major studios and for producing high-profile projects across network TV and Hollywood.
  • D. Barbara Siegel
    Barbara Siegel is an American author best known for co-writing numerous science fiction and fantasy novels and game-related books, often in collaboration with her husband Scott Siegel.
  • E. Janet Margolin
    Janet Margolin was an American film and television actress best known for her roles in movies such as "David and Lisa" and Woody Allen's "Annie Hall."
  • 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_69aed93c69208190a4efac0efe3cd69b completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefbd7896c81909c61ed0d910d9c5f completed March 9, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9c31748c81909477e01261b5a78a completed March 21, 2026, 1:25 p.m.
Created at: March 9, 2026, 3:38 p.m.