Triple

T13606863
Position Surface form Disambiguated ID Type / Status
Subject Fanny Ardant E325084 entity
Predicate name P16 FINISHED
Object Fanny Ardant E325084 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: Fanny Ardant | Statement: [Fanny Ardant, name, Fanny Ardant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fanny Ardant
Context triple: [Fanny Ardant, name, Fanny Ardant]
  • A. Fanny Ardant chosen
    Fanny Ardant is a renowned French actress known for her sophisticated screen presence and acclaimed performances in European cinema and theater.
  • B. Marylène Ferrand
    Marylène Ferrand is a French landscape architect known for her role in designing Paris’s Parc de Bercy.
  • C. Béatrice Dalle
    Béatrice Dalle is a French actress known for her intense, unconventional screen presence and breakout role in the 1986 film "Betty Blue."
  • D. Carole Bouquet
    Carole Bouquet is a French actress known for her roles in European art cinema and as a Bond girl in the James Bond film "For Your Eyes Only."
  • E. Marina Foïs
    Marina Foïs is a French actress known for her versatile performances in film, television, and theater, and for being a prominent figure in contemporary French cinema.
  • 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb07e442c819086a8cbb967c03ad3 completed April 12, 2026, 2:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77f96280881908bab3af5c80f6d55 completed May 3, 2026, 5:02 p.m.
Created at: April 9, 2026, 9:50 p.m.