Triple

T11291959
Position Surface form Disambiguated ID Type / Status
Subject Eduardo Cansino E267345 entity
Predicate spouse P13 FINISHED
Object Volga Hayworth E277752 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: Volga Hayworth | Statement: [Eduardo Cansino, spouse, Volga Hayworth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Volga Hayworth
Context triple: [Eduardo Cansino, spouse, Volga Hayworth]
  • A. Volga Hayworth chosen
    Volga Hayworth was the mother of Hollywood actress Rita Hayworth and part of the family background that shaped the star's early life.
  • B. Carole Landis
    Carole Landis was an American film actress and World War II pin-up star known for her glamorous screen presence in 1940s Hollywood.
  • C. Jo Harlow
    Jo Harlow is a technology executive best known for leading mobile device and smartphone businesses at companies such as Nokia and later Microsoft.
  • D. Alice Faye
    Alice Faye was an American actress and singer best known as a 1930s–1940s Hollywood musical star at 20th Century Fox.
  • E. Vina Wray
    Vina Wray is an alternate name for Fay Wray, the Canadian-American actress best known for her iconic role in the 1933 film "King Kong."
  • 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_69d6aac993a08190a6f36445ebaf9a43 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e989fdac81909a4a75f1f68b55c6 completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5b7b051988190abec04740df75c89 completed April 20, 2026, 5:20 a.m.
Created at: April 8, 2026, 9:32 p.m.