Triple

T17065804
Position Surface form Disambiguated ID Type / Status
Subject Billie Frechette E414082 entity
Predicate portrayedBy P1507 FINISHED
Object Marion Cotillard E135915 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: Marion Cotillard | Statement: [Billie Frechette, portrayedBy, Marion Cotillard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marion Cotillard
Context triple: [Billie Frechette, portrayedBy, Marion Cotillard]
  • A. Marion Cotillard chosen
    Marion Cotillard is an acclaimed French actress known for her versatile performances in both French and Hollywood films, including her Oscar-winning role in "La Vie en Rose."
  • B. Bérénice Bejo
    Bérénice Bejo is a French-Argentine actress best known internationally for her acclaimed performance in the silent film "The Artist."
  • C. Juliette Binoche
    Juliette Binoche is an acclaimed French actress known for her nuanced performances in international cinema and her Academy Award-winning role in "The English Patient."
  • D. Jean-Marie Binoche
    Jean-Marie Binoche is a French actor and director best known as the father of acclaimed actress Juliette Binoche.
  • E. Cate Blanchett
    Cate Blanchett is an acclaimed Australian actress renowned for her versatile performances in both independent films and major Hollywood productions, earning numerous awards including Oscars, Golden Globes, and BAFTAs.
  • 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_69d886cde3d481908d4d01ba88ba7eb7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3db8171348190ab68d2e4f05f7120 completed April 18, 2026, 7:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01234e9a94819094618ba43b7d22b4 completed May 11, 2026, 12:31 a.m.
Created at: April 10, 2026, 5:34 a.m.