Triple

T3009663
Position Surface form Disambiguated ID Type / Status
Subject The Bank Job E81985 entity
Predicate cinematographyBy P1953 FINISHED
Object Michael Coulter E68507 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 Coulter | Statement: [The Bank Job, cinematographyBy, Michael Coulter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Coulter
Context triple: [The Bank Job, cinematographyBy, Michael Coulter]
  • A. Michael Coulter chosen
    Michael Coulter is a British cinematographer known for his work on popular films including the romantic comedy "Love Actually."
  • B. Jimmy Yuill
    Jimmy Yuill is a Scottish actor known for his work in film, television, and theatre, including roles in several Shakespearean adaptations.
  • C. Macaulay Connor
    Macaulay Connor is the fictional cynical reporter and love interest in Philip Barry’s play "The Philadelphia Story," later portrayed by James Stewart in the classic 1940 film adaptation.
  • D. Daniel Millar
    Daniel Millar is an actor known for his role in the National Theatre’s acclaimed stage production of "Frankenstein."
  • E. Christopher Young
    Christopher Young is an American film composer renowned for his atmospheric and often darkly dramatic scores across horror, thriller, and action movies.
  • 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_69ad8b1c4de88190a83b7cefaa1f2842 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a4ccbf08190a7580c9e758804d0 completed March 8, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e5f612c8190824deb0813a9f981 completed March 11, 2026, 8:57 a.m.
Created at: March 8, 2026, 3 p.m.