Triple

T1557263
Position Surface form Disambiguated ID Type / Status
Subject Lupe Vélez E33234 entity
Predicate name P16 FINISHED
Object Lupe Vélez E33234 NE FINISHED

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: [Lupe Vélez, name, Lupe Vélez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lupe Vélez
Context triple: [Lupe Vélez, name, 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. Isabelle Ferrer
    Isabelle Ferrer is a French woman best known for being the former wife of legendary footballer and actor Eric Cantona.
  • C. Bertha Navarro
    Bertha Navarro is a Mexican film producer best known for her long-time collaboration with director Guillermo del Toro on acclaimed genre and art-house films.
  • D. Haydée Santamaría
    Haydée Santamaría was a Cuban revolutionary and cultural figure, a founding member of the 26th of July Movement and longtime director of the Casa de las Américas.
  • E. Rita Moreno
    Rita Moreno is a trailblazing Puerto Rican–American actress, singer, and dancer renowned for her groundbreaking, award-winning career across film, television, and theater.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a885ef9cf48190b0af0f5ce3d02231 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908704d208190937af41c6454df4e completed March 5, 2026, 4:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad3710688c8190a280f03bced5601f completed March 8, 2026, 8:45 a.m.
Created at: March 4, 2026, 7:27 p.m.