Triple

T12686139
Position Surface form Disambiguated ID Type / Status
Subject Polisse E303071 entity
Predicate starring P1507 FINISHED
Object Sandrine Kiberlain E574929 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: Sandrine Kiberlain | Statement: [Polisse, starring, Sandrine Kiberlain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sandrine Kiberlain
Context triple: [Polisse, starring, Sandrine Kiberlain]
  • A. Sandrine Kiberlain chosen
    Sandrine Kiberlain is a French actress and singer known for her acclaimed performances in both dramatic and comedic films.
  • B. Nelly Auteuil
    Nelly Auteuil is the daughter of French actor and filmmaker Daniel Auteuil.
  • C. Sandrine Holt
    Sandrine Holt is a Canadian actress known for her roles in film and television, including appearances in genre franchises and high-profile dramas.
  • D. Virginie Ledoyen
    Virginie Ledoyen is a French actress known for her work in both French cinema and international films, including prominent roles in dramas and thrillers.
  • E. Ludivine Sagnier
    Ludivine Sagnier is a French actress known for her versatile performances in both art-house and mainstream films, as well as in international television series.
  • 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_69d7bdee64a08190801c6d470aefd723 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961d7cd4c81909521839ef5859799 completed April 10, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b8a79488190aaf95d4f2e20a7bc completed May 3, 2026, 12:49 a.m.
Created at: April 9, 2026, 5:21 p.m.