Triple

T9428557
Position Surface form Disambiguated ID Type / Status
Subject Dancer in the Dark E227315 entity
Predicate characterPortrayedBy P1507 FINISHED
Object Kathy – Catherine Deneuve E256268 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: Kathy – Catherine Deneuve | Statement: [Dancer in the Dark, characterPortrayedBy, Kathy – Catherine Deneuve]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kathy – Catherine Deneuve
Context triple: [Dancer in the Dark, characterPortrayedBy, Kathy – Catherine Deneuve]
  • A. Brigitte
    Brigitte is a French former teacher best known as the wife of Emmanuel Macron, the President of France.
  • B. Cécile – Marie Trintignant
    Cécile – Marie Trintignant was a French actress known for her intense, emotionally charged performances in film, television, and theater.
  • C. Catherine Deneuve chosen
    Catherine Deneuve is a renowned French actress celebrated for her cool, enigmatic screen presence and iconic roles in European cinema since the 1960s.
  • D. Françoise Rosay
    Françoise Rosay was a prominent French stage and film actress known for her powerful character roles in European cinema from the 1920s through the 1950s.
  • E. Emmanuelle Béart
    Emmanuelle Béart is a French actress acclaimed for her performances in films such as "Manon des Sources" and "Mission: Impossible."
  • 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_69ca8436ba308190903e470776d2d893 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd7c92ee848190baa41fe91a131305 completed April 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69d11034369c81908992e268e66d7833 completed April 4, 2026, 1:20 p.m.
Created at: March 30, 2026, 7:49 p.m.