Triple

T17435105
Position Surface form Disambiguated ID Type / Status
Subject La Famille Bélier E423981 entity
Predicate producer P490 FINISHED
Object Stéphane Célérier
Stéphane Célérier is a French film producer known for backing successful and popular French-language films.
E1371937 NE FINISHED

How this triple was built (4 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: Stéphane Célérier | Statement: [La Famille Bélier, producer, Stéphane Célérier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stéphane Célérier
Context triple: [La Famille Bélier, producer, Stéphane Célérier]
  • A. Stéphane Séjourné
    Stéphane Séjourné is a French politician and Member of the European Parliament closely associated with President Emmanuel Macron’s centrist political movement.
  • B. Laurent Chalumeau
    Laurent Chalumeau is a French writer and screenwriter known for his work in film and literature.
  • C. Christophe Pélissier
    Christophe Pélissier is a French football coach known for guiding modest clubs to promotion in the French league system.
  • D. Stéphane Loda
    Stéphane Loda is a French local politician who serves as the mayor of the Mediterranean coastal commune of Canet-en-Roussillon.
  • E. Laurent Brosse
    Laurent Brosse is a French local politician who serves as the mayor of the suburban Parisian town of Conflans-Sainte-Honorine.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Stéphane Célérier
Triple: [La Famille Bélier, producer, Stéphane Célérier]
Generated description
Stéphane Célérier is a French film producer known for backing successful and popular French-language films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Stéphane Célérier
Target entity description: Stéphane Célérier is a French film producer known for backing successful and popular French-language films.
  • A. Stéphane Séjourné
    Stéphane Séjourné is a French politician and Member of the European Parliament closely associated with President Emmanuel Macron’s centrist political movement.
  • B. Laurent Chalumeau
    Laurent Chalumeau is a French writer and screenwriter known for his work in film and literature.
  • C. Christophe Pélissier
    Christophe Pélissier is a French football coach known for guiding modest clubs to promotion in the French league system.
  • D. Stéphane Loda
    Stéphane Loda is a French local politician who serves as the mayor of the Mediterranean coastal commune of Canet-en-Roussillon.
  • E. Laurent Brosse
    Laurent Brosse is a French local politician who serves as the mayor of the suburban Parisian town of Conflans-Sainte-Honorine.
  • F. None of above. chosen

Provenance (5 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_69d889d88b6081908bada047f5b3ba51 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4490361c081908fd24f9a812f212c completed April 19, 2026, 3:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0723ef338c819084b9f2d04aea4290 completed May 15, 2026, 1:47 p.m.
NEDg Description generation batch_6a07256bcabc819090f9a13046df763f completed May 15, 2026, 1:53 p.m.
NED2 Entity disambiguation (via description) batch_6a0726306be48190962cb5eebb214136 completed May 15, 2026, 1:57 p.m.
Created at: April 10, 2026, 5:46 a.m.