Triple

T23492123
Position Surface form Disambiguated ID Type / Status
Subject Ladies’ Day E570703 entity
Predicate starring P1507 FINISHED
Object Lupe Vélez 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: Lupe Vélez | Statement: [Ladies’ Day, starring, Lupe Vélez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lupe Vélez
Context triple: [Ladies’ Day, starring, Lupe Vélez]
  • A. Lupe Vélez chosen
    Lupe Vélez was a Mexican-born Hollywood actress and comedian of the 1920s and 1930s, known for her vibrant screen presence and roles in both silent films and early talkies.
  • B. Carmen Infante
    Carmen Infante is a notable individual bearing the Infante surname, recognized enough to be specifically cited among its distinguished bearers.
  • C. Rosa Vázquez
    Rosa Vázquez is the mother of Puerto Rican reggaeton artist Ñengo Flow.
  • D. Concha Méndez
    Concha Méndez was a Spanish poet, playwright, and publisher associated with the avant-garde Generation of ’27, known for her innovative, feminist writing and cultural activism during the early 20th century.
  • E. Mimi Valdés
    Mimi Valdés is an American music and film executive and producer known for her creative leadership at Pharrell Williams’ i am OTHER and her work on projects across film, television, and music.
  • 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_69e245b0b01481908f636939bedd804c completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a7dd56408190b459077e433ed1c3 completed April 29, 2026, 6:40 a.m.
Created at: April 17, 2026, 6:05 p.m.