Triple
T15199125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Another Country |
E363217
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Peter Biziou |
—
|
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: Peter Biziou | Statement: [Another Country, cinematographyBy, Peter Biziou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Biziou Context triple: [Another Country, cinematographyBy, Peter Biziou]
-
A.
Peter Biziou
chosen
Peter Biziou is a British cinematographer known for his work on films such as "Bugsy Malone" and the Oscar-winning "Mississippi Burning."
-
B.
Olivier Delbosc
Olivier Delbosc is a French film producer known for his work on numerous acclaimed arthouse and independent films.
-
C.
Michel Bizot
Michel Bizot is a Paris Métro station in the 12th arrondissement, named after the 19th-century French general Michel Brice Bizot.
-
D.
Jean-Michel Defaye
Jean-Michel Defaye is a French composer and trombonist known for his film scores and brass music, particularly for trombone.
-
E.
Patrice Bessac
Patrice Bessac is a French politician known for serving as the mayor of Montreuil, a suburb of Paris.
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b476208190a5119710c518bb1f |
completed | April 15, 2026, 9:44 p.m. |
Created at: April 10, 2026, 3:10 a.m.