Triple

T20147797
Position Surface form Disambiguated ID Type / Status
Subject Anita Ekberg E491350 entity
Predicate name P16 FINISHED
Object Anita Ekberg NE NERFINISHED

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: Anita Ekberg | Statement: [Anita Ekberg, name, Anita Ekberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anita Ekberg
Context triple: [Anita Ekberg, name, Anita Ekberg]
  • A. Anita Ekberg chosen
    Anita Ekberg was a Swedish actress and former model best known for her iconic role in Federico Fellini’s film "La Dolce Vita."
  • B. Anna Karina
    Anna Karina was a Danish-French actress, singer, and fashion icon best known as a muse of the French New Wave and for her acclaimed performances in films such as "A Woman Is a Woman" and "Pierrot le Fou."
  • C. Gina Lollobrigida
    Gina Lollobrigida was an iconic Italian film actress and international sex symbol of the 1950s and 1960s who later became a photojournalist and sculptor.
  • D. Brigitte Bardot
    Brigitte Bardot is a French former film actress and sex symbol of the 1950s and 1960s who later became a prominent animal rights activist.
  • E. Brigitte Helm
    Brigitte Helm was a German actress best known for her iconic dual role as Maria and the Maschinenmensch in Fritz Lang’s pioneering science fiction film "Metropolis."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6265f8f0819080b29c752a574088 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e667a0075c8190a5c4de53a0caa7f6 completed April 20, 2026, 5:51 p.m.
Created at: April 11, 2026, 11:33 p.m.