Triple

T21906069
Position Surface form Disambiguated ID Type / Status
Subject Carmen (1983 film) E540940 entity
Predicate starring P1507 FINISHED
Object Cristina Hoyos 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: Cristina Hoyos | Statement: [Carmen (1983 film), starring, Cristina Hoyos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cristina Hoyos
Context triple: [Carmen (1983 film), starring, Cristina Hoyos]
  • A. Cristina Hoyos chosen
    Cristina Hoyos is a renowned Spanish flamenco dancer, choreographer, and actress celebrated for her influential performances on stage and in film.
  • B. Cristina Villanueva
    Cristina Villanueva is known as the wife of Eraño G. Manalo, the late Executive Minister of the Iglesia ni Cristo, a major Philippine-based Christian church.
  • C. Cristina Banegas
    Cristina Banegas is an acclaimed Argentine actress and director recognized internationally for her powerful performances in film, television, and theater.
  • D. Luli Arroyo-Bernas
    Luli Arroyo-Bernas is a Filipino public figure known as the daughter of former Philippine President Gloria Macapagal Arroyo and for her involvement in civic and social initiatives.
  • E. Michelle Bonilla
    Michelle Bonilla is an American actress known for her work in television and film, including roles on popular series such as ER and The Closer.
  • 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_69e0c47b4e8c81908c8076eaa4c8e4f2 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f121d62a648190af7074251dc6a03a completed April 28, 2026, 9:08 p.m.
Created at: April 16, 2026, 7:36 p.m.