Triple

T16761019
Position Surface form Disambiguated ID Type / Status
Subject The Young Girls of Rochefort E407342 entity
Predicate stars P1956 FINISHED
Object Danielle Darrieux E890814 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: Danielle Darrieux | Statement: [The Young Girls of Rochefort, stars, Danielle Darrieux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danielle Darrieux
Context triple: [The Young Girls of Rochefort, stars, Danielle Darrieux]
  • A. Danielle Darrieux chosen
    Danielle Darrieux was a celebrated French actress and singer whose career spanned over eight decades, making her one of France’s most enduring and versatile film stars.
  • B. Simone Signoret
    Simone Signoret was an acclaimed French actress and Academy Award winner, renowned for her powerful performances in mid-20th-century European cinema.
  • C. Annie Girardot
    Annie Girardot was a celebrated French film and theater actress known for her emotionally powerful performances and enduring popularity from the 1960s through the 1990s.
  • D. Hélène Brion
    Hélène Brion was a French feminist, pacifist, and trade unionist known for her activism during and after World War I.
  • E. Marie Trintignant
    Marie Trintignant was a French actress known for her intense, emotionally charged performances in film, television, and theater before her life was tragically cut short.
  • 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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3abec638c81909d71ff452a4123c9 completed April 18, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00aaf7908481909af31fc2d02f33fb completed May 10, 2026, 3:57 p.m.
Created at: April 10, 2026, 5:21 a.m.