Triple

T15033467
Position Surface form Disambiguated ID Type / Status
Subject Brazil (1985 film) E378416 entity
Predicate editedBy P1954 FINISHED
Object Julian Doyle E357148 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: Julian Doyle | Statement: [Brazil (1985 film), editedBy, Julian Doyle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Julian Doyle
Context triple: [Brazil (1985 film), editedBy, Julian Doyle]
  • A. Julian Doyle chosen
    Julian Doyle is a British film editor and director best known for his long-time collaboration with the Monty Python team on several of their films.
  • B. Jack Doolan
    Jack Doolan is a British actor best known for his role in the coming-of-age comedy-drama film "Cemetery Junction" and various appearances in UK television series.
  • C. Jules O'Loughlin
    Jules O'Loughlin is an Australian cinematographer known for his work on films such as the 2015 horror-comedy "Krampus."
  • D. Julian Reid
    Julian Reid is a relatively obscure individual whose specific public notability is not clearly established from the available information.
  • E. Luke Doolan
    Luke Doolan is an Australian film editor and filmmaker best known for his work on acclaimed films such as "Animal Kingdom."
  • 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_69d85cd46b2c819090d054c27787f677 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7e3a7c8819081f26c2435c1bcb2 completed April 15, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9dddd0208190b2dac7a078de2931 completed May 9, 2026, 2:37 a.m.
Created at: April 10, 2026, 2:59 a.m.