Triple

T18401361
Position Surface form Disambiguated ID Type / Status
Subject Berkely Mather E450002 entity
Predicate collaboratedWith P435 FINISHED
Object Richard Maibaum 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: Richard Maibaum | Statement: [Berkely Mather, collaboratedWith, Richard Maibaum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Richard Maibaum
Context triple: [Berkely Mather, collaboratedWith, Richard Maibaum]
  • A. Richard Maibaum chosen
    Richard Maibaum was an American screenwriter and producer best known for his long-running work on the James Bond film series.
  • B. Michael C. Gross
    Michael C. Gross was an American film producer and art director best known for his work on the Ghostbusters franchise and other popular comedies of the 1980s and early 1990s.
  • C. Lloyd Levin
    Lloyd Levin is an American film producer known for his work on major genre films such as "Hellboy II: The Golden Army," "Watchmen," and "United 93."
  • D. David Kershner
    David Kershner is the son of American film director Irvin Kershner, known for his work in the movie industry.
  • E. Russell Carpenter
    Russell Carpenter is an Academy Award–winning American cinematographer best known for his work on major films such as Titanic and other high-profile Hollywood productions.
  • 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_69d8b9fab8a8819086a9ddc0871715e0 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e5195185b08190bd3b5471cdc047b0 completed April 19, 2026, 6:05 p.m.
Created at: April 10, 2026, 10:46 a.m.