Triple
T19737220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brazil (film) |
E474017
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | Julian Doyle |
—
|
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: Julian Doyle | Statement: [Brazil (film), editor, Julian Doyle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julian Doyle Context triple: [Brazil (film), editor, 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 (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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6515ea688819097b6838e6a3b3d4a |
completed | April 20, 2026, 4:16 p.m. |
Created at: April 10, 2026, 1:47 p.m.