Triple

T3358244
Position Surface form Disambiguated ID Type / Status
Subject Kiss Kiss Bang Bang E70655 entity
Predicate cinematographyBy P1953 FINISHED
Object Michael Barrett E104613 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: Michael Barrett | Statement: [Kiss Kiss Bang Bang, cinematographyBy, Michael Barrett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Barrett
Context triple: [Kiss Kiss Bang Bang, cinematographyBy, Michael Barrett]
  • A. Michael Barrett chosen
    Michael Barrett is an American cinematographer known for his work on numerous feature films and television projects, including mainstream comedies and action movies.
  • B. Craig Barrett
    Craig Barrett is an American business executive and engineer best known for serving as CEO and chairman of Intel Corporation.
  • C. Michael Byrne
    Michael Byrne is a British character actor known for his numerous film and television roles, often portraying military officers or authority figures.
  • D. Larry Barrett
    Larry Barrett was one of the judges who scored the historic 1975 heavyweight boxing match between Muhammad Ali and Joe Frazier, known as the "Thrilla in Manila."
  • E. Michael Costigan
    Michael Costigan is a film and television producer known for his work on various high-profile projects, including serving as an executive producer on the miniseries "A Teacher."
  • 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_69ad85a660c48190998489309a3b4869 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb26523cc819091006fde7beb32e4 completed March 8, 2026, 5:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5281788fc81908baa6a14098281b4 completed March 14, 2026, 9:19 a.m.
Created at: March 8, 2026, 3:13 p.m.