Triple

T10124351
Position Surface form Disambiguated ID Type / Status
Subject Mississippi Burning E226174 entity
Predicate cinematographer P1953 FINISHED
Object Peter Biziou E235553 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: Peter Biziou | Statement: [Mississippi Burning, cinematographer, Peter Biziou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Biziou
Context triple: [Mississippi Burning, cinematographer, 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. Jean-Michel Defaye
    Jean-Michel Defaye is a French composer and trombonist known for his film scores and brass music, particularly for trombone.
  • C. Patrice Bessac
    Patrice Bessac is a French politician known for serving as the mayor of Montreuil, a suburb of Paris.
  • D. Jean-Pierre Blazy
    Jean-Pierre Blazy is a French politician known for serving as the long-time mayor of the suburban Parisian commune of Gonesse.
  • E. Guy Billout
    Guy Billout is a French illustrator and graphic artist renowned for his surreal, meticulously detailed illustrations that often feature ironic or thought-provoking twists.
  • 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_69ca843057b48190a86730167f5d6b98 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cdd2ebe4548190a484c145639d92f0 completed April 2, 2026, 2:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69f64b78e7ec819093e5e631197ed295 completed May 2, 2026, 7:07 p.m.
Created at: March 30, 2026, 9:05 p.m.