Triple

T17340533
Position Surface form Disambiguated ID Type / Status
Subject Two English Girls E421053 entity
Predicate castMember P1668 FINISHED
Object Marie-France Pisier NE ONNED1

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: Marie-France Pisier | Statement: [Two English Girls, castMember, Marie-France Pisier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marie-France Pisier
Context triple: [Two English Girls, castMember, Marie-France Pisier]
  • A. Marie-France Pisier chosen
    Marie-France Pisier was a French actress and screenwriter renowned for her work in auteur cinema from the 1960s onward, notably in films by François Truffaut and André Téchiné.
  • B. Marie-José Nat
    Marie-José Nat was a French film and television actress known for her nuanced performances in mid-20th-century European cinema.
  • C. Carine Petit
    Carine Petit is a French politician who serves as the mayor of Paris's 14th arrondissement.
  • D. Marie-José Pérec
    Marie-José Pérec is a French sprinter and three-time Olympic champion, best known for dominating the 200m and 400m events in the 1990s.
  • E. Marie-France Grange
    Marie-France Grange is a person notable enough to be recognized as a significant bearer of the surname Grange.
  • 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_69d889d3adc881909319f1edb8d2a956 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a15f6488190ad7d489e7391ab12 completed April 19, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a019552a0208190bd8bd0f9588911c3 in_progress May 11, 2026, 8:37 a.m.
Created at: April 10, 2026, 5:44 a.m.