Triple

T4764021
Position Surface form Disambiguated ID Type / Status
Subject What Price Glory E105764 entity
Predicate stars P1956 FINISHED
Object Dolores del Río E224452 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: Dolores del Río | Statement: [What Price Glory, stars, Dolores del Río]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dolores del Río
Context triple: [What Price Glory, stars, Dolores del Río]
  • A. Dolores del Río chosen
    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.
  • B. Margarita Carmen Cansino
    Margarita Carmen Cansino, better known as Rita Hayworth, was a celebrated American film actress and dancer who became one of Hollywood’s most iconic screen goddesses of the 1940s.
  • C. Isabelle Ferrer
    Isabelle Ferrer is a French woman best known for being the former wife of legendary footballer and actor Eric Cantona.
  • D. Katy Jurado
    Katy Jurado was a pioneering Mexican actress who achieved international fame in Hollywood Westerns and became the first Latin American woman to win a Golden Globe.
  • E. Nina Foch
    Nina Foch was a Dutch-born American actress known for her poised, often aristocratic roles in classic Hollywood films and for her work as a respected acting teacher.
  • 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_69bd43f14cac819081c7c69803648211 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6530f0648190b76db9964471cfeb completed March 20, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69be3a87741081909380c51ba4efed92 completed March 21, 2026, 6:28 a.m.
Created at: March 20, 2026, 1:21 p.m.