Triple

T22051788
Position Surface form Disambiguated ID Type / Status
Subject Le Vieux Fusil E544901 entity
Predicate character P662 FINISHED
Object Julien Dandieu 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: Julien Dandieu | Statement: [Le Vieux Fusil, character, Julien Dandieu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Julien Dandieu
Context triple: [Le Vieux Fusil, character, Julien Dandieu]
  • A. Julien Dandieu chosen
    Julien Dandieu is the protagonist of the French film "Le Vieux Fusil," a country doctor whose life is shattered by wartime atrocities, driving him to a desperate quest for vengeance.
  • B. Julien Rappeneau
    Julien Rappeneau is a French screenwriter and film director known for his work on popular contemporary French films, including thrillers and character-driven dramas.
  • C. Laurent Durand
    Laurent Durand was an 18th-century French publisher and bookseller best known for helping to produce the influential Enlightenment-era Encyclopédie.
  • D. Frédéric Dambier
    Frédéric Dambier is a French former competitive figure skater best known for his success in European and international competitions in the early 2000s.
  • E. Dimitri Rataud
    Dimitri Rataud is a French voice actor known for his role in the animated film "White Fang" (2018).
  • 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_69e11e32445c8190ab97089b48a130bb completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1285513fc8190b691e1f57085956f completed April 28, 2026, 9:36 p.m.
Created at: April 16, 2026, 8:26 p.m.