Triple

T20183509
Position Surface form Disambiguated ID Type / Status
Subject Anaconda (1997 film) E492792 entity
Predicate cinematography P1953 FINISHED
Object Bill Butler 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: Bill Butler | Statement: [Anaconda (1997 film), cinematography, Bill Butler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bill Butler
Context triple: [Anaconda (1997 film), cinematography, Bill Butler]
  • A. Bill Butler chosen
    Bill Butler was an acclaimed American cinematographer best known for his influential work on landmark films of the 1970s and 1980s.
  • B. Steve Butler
    Steve Butler is a fictional character portrayed by Tommy Lee Jones in the film "Heaven & Earth."
  • C. John R. Butler
    John R. Butler was a notable individual interred at El Camino Memorial Park, recognized enough in his community or field to be listed among the cemetery’s distinguished burials.
  • D. Reg Butler
    Reg Butler was a British sculptor known for his expressive, often skeletal metal figures and his prominence in postwar European modernist sculpture.
  • E. Joe Butler
    Joe Butler is a film editor best known for his work on the animated feature "Ron’s Gone Wrong."
  • 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_69da6268a034819081cbd9ea5a1c9475 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e668f068748190a0941e98ef5afd59 completed April 20, 2026, 5:57 p.m.
Created at: April 11, 2026, 11:36 p.m.