Triple

T22311757
Position Surface form Disambiguated ID Type / Status
Subject Norma Aleandro E551532 entity
Predicate name P16 FINISHED
Object Norma Aleandro 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: Norma Aleandro | Statement: [Norma Aleandro, name, Norma Aleandro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norma Aleandro
Context triple: [Norma Aleandro, name, Norma Aleandro]
  • A. Norma Aleandro chosen
    Norma Aleandro is an acclaimed Argentine actress, screenwriter, and director, widely regarded as one of Latin America's most important film and theater performers.
  • B. Adriana Paz
    Adriana Paz is a Mexican actress known for her acclaimed performances in contemporary Latin American cinema and television.
  • C. Silvia Pinal
    Silvia Pinal is a renowned Mexican actress and producer, celebrated for her work in classic Mexican cinema and her collaborations with director Luis Buñuel.
  • D. Josefa Ferrer
    Josefa Ferrer is an actress known for playing the character Maria.
  • E. Carmen Bravo
    Carmen Bravo was a Spanish pianist best known for her interpretations of 20th-century repertoire and her close association with the music of her husband, composer Federico Mompou.
  • 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_69e11e4776588190abb21e5cea79973f completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1574f97cc81909685aeef15d02af9 completed April 29, 2026, 12:56 a.m.
Created at: April 16, 2026, 8:42 p.m.