Triple

T17769334
Position Surface form Disambiguated ID Type / Status
Subject Michelle Salas E443590 entity
Predicate hasRelative P367 FINISHED
Object Silvia Pinal 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: Silvia Pinal | Statement: [Michelle Salas, hasRelative, Silvia Pinal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Silvia Pinal
Context triple: [Michelle Salas, hasRelative, Silvia Pinal]
  • A. Silvia Pinal chosen
    Silvia Pinal is a renowned Mexican actress and producer, celebrated for her work in classic Mexican cinema and her collaborations with director Luis Buñuel.
  • B. Sara García
    Sara García was a legendary Mexican film actress, famously known as the “Grandmother of Mexican Cinema” for her iconic maternal roles in classic Golden Age movies.
  • C. Norma Aleandro
    Norma Aleandro is an acclaimed Argentine actress, screenwriter, and director, widely regarded as one of Latin America's most important film and theater performers.
  • D. Adriana Paz
    Adriana Paz is a Mexican actress known for her acclaimed performances in contemporary Latin American cinema and television.
  • E. Katy Jurado
    Katy Jurado was a pioneering Mexican actress who achieved international fame in Hollywood Westerns and became the first Latin American woman to win a Golden Globe.
  • 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_69d8b9edf16c8190a59ebd245d378f4f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e485fe70648190b4107e1eabacc694 completed April 19, 2026, 7:36 a.m.
Created at: April 10, 2026, 10:11 a.m.