Triple

T9846259
Position Surface form Disambiguated ID Type / Status
Subject Jules and Jim E239348 entity
Predicate producer P490 FINISHED
Object Marcel Berbert E820587 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: Marcel Berbert | Statement: [Jules and Jim, producer, Marcel Berbert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marcel Berbert
Context triple: [Jules and Jim, producer, Marcel Berbert]
  • A. Marcel Berbert chosen
    Marcel Berbert was a French film producer known for his collaborations with prominent directors such as François Truffaut during the mid-20th century.
  • B. Bruno Barbey
    Bruno Barbey was a renowned French-Moroccan photojournalist celebrated for his vivid color photography and extensive work documenting political unrest and cultural life around the world.
  • C. Boris Dilliès
    Boris Dilliès is a Belgian politician known for serving as the mayor of the Brussels municipality of Uccle.
  • D. Marcel Weber
    Marcel Weber is a personal name shared by multiple individuals, most commonly of German-speaking or Swiss origin, and may refer to various figures in fields such as sports, academia, or the arts.
  • E. Jules Repond
    Jules Repond was a Swiss military officer best known for redesigning and modernizing the distinctive Renaissance-style uniforms of the Vatican's Swiss Guard in the early 20th century.
  • 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_69ca84e3f0c48190ada72a65ebd50efd completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb36156308190b26892702f3b41e0 completed April 2, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20d4079048190976eb198f8ef62f0 completed April 5, 2026, 7:20 a.m.
Created at: March 30, 2026, 8:34 p.m.