Triple

T5850393
Position Surface form Disambiguated ID Type / Status
Subject Michel Serrault E130013 entity
Predicate name P16 FINISHED
Object Michel Serrault E130013 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: Michel Serrault | Statement: [Michel Serrault, name, Michel Serrault]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michel Serrault
Context triple: [Michel Serrault, name, Michel Serrault]
  • A. Michel Serrault chosen
    Michel Serrault was a celebrated French actor known for his versatile performances in film, theater, and television, particularly his iconic role in "La Cage aux Folles."
  • B. Joseph Noiret
    Joseph Noiret was a Belgian poet, painter, and art critic best known as a founding figure of the postwar avant-garde COBRA movement.
  • C. Philippe Noiret
    Philippe Noiret was a renowned French film and stage actor celebrated for his versatile performances in classics such as "Cinema Paradiso" and "Il Postino."
  • D. Michel Simon
    Michel Simon was a renowned Swiss-born French actor celebrated for his expressive character roles in classic European cinema from the 1920s through the 1960s.
  • E. Alain Chabat
    Alain Chabat is a French actor, comedian, director, and screenwriter known for his influential work in French comedy and films such as "Asterix & Obelix: Mission Cleopatra."
  • 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_69c0084de39081909eb34e6bed74215a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03515dc0c81908797a9713f1a603f completed March 22, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c113464f7481909538a1f2ef05216c completed March 23, 2026, 10:17 a.m.
Created at: March 22, 2026, 3:55 p.m.