Triple

T21691087
Position Surface form Disambiguated ID Type / Status
Subject Miss Golden Globe E535369 entity
Predicate hasNotableFormerTitleholder P59714 FINISHED
Object Francesca Eastwood 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: Francesca Eastwood | Statement: [Miss Golden Globe, hasNotableFormerTitleholder, Francesca Eastwood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Francesca Eastwood
Context triple: [Miss Golden Globe, hasNotableFormerTitleholder, Francesca Eastwood]
  • A. Francesca Eastwood chosen
    Francesca Eastwood is an American actress, model, and television personality, and the daughter of filmmaker Clint Eastwood.
  • B. Kimber Lynn Eastwood
    Kimber Lynn Eastwood is an American film producer, makeup artist, and the daughter of actor-director Clint Eastwood.
  • C. Alison Eastwood
    Alison Eastwood is an American actress, director, and fashion model, and the daughter of filmmaker Clint Eastwood.
  • D. Rosanna Arquette
    Rosanna Arquette is an American actress and filmmaker known for her roles in films such as "Desperately Seeking Susan" and "Pulp Fiction."
  • E. Kathryn Eastwood
    Kathryn Eastwood is an American actress and screenwriter, best known as one of Clint Eastwood’s daughters and for her roles in several independent films.
  • 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_69e0c46a6ee481908836e1420fb78c9b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef96cfaab08190b400e1538afc8c43 completed April 27, 2026, 5:03 p.m.
Created at: April 16, 2026, 6:45 p.m.