Triple

T18135670
Position Surface form Disambiguated ID Type / Status
Subject Pedro Armendáriz E434128 entity
Predicate workedWith P398 FINISHED
Object María Félix 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: María Félix | Statement: [Pedro Armendáriz, workedWith, María Félix]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: María Félix
Context triple: [Pedro Armendáriz, workedWith, María Félix]
  • A. María Félix chosen
    María Félix was an iconic Mexican film actress and enduring symbol of the Golden Age of Mexican cinema, renowned for her commanding screen presence and strong, independent characters.
  • B. Dolores del Río
    Dolores del Río was a pioneering Mexican actress and international film star of the 1920s–1940s, celebrated as one of Hollywood’s first major Latina leading ladies.
  • 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. 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.
  • E. Josefa Ferrer
    Josefa Ferrer is an actress known for playing the character Maria.
  • 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_69d8b909e8cc81908df4cc2b8ea6d11f completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4de0677088190aaf584882b3d74a1 completed April 19, 2026, 1:52 p.m.
Created at: April 10, 2026, 10:29 a.m.