Triple

T10945023
Position Surface form Disambiguated ID Type / Status
Subject Vina Wray E258572 entity
Predicate alternateName P39 FINISHED
Object Fay Wray E4506 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: Fay Wray | Statement: [Vina Wray, alternateName, Fay Wray]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fay Wray
Context triple: [Vina Wray, alternateName, Fay Wray]
  • A. Fay Wray chosen
    Fay Wray was a Canadian-American actress best known for her iconic role as the damsel Ann Darrow in the classic 1933 film "King Kong."
  • B. Maureen O'Brien
    Maureen O'Brien is a British actress best known for playing the First Doctor’s companion Vicki in the classic science fiction television series Doctor Who.
  • C. Colleen Moore
    Colleen Moore was a popular American silent film actress best known for her flapper roles in the 1920s, which helped define the era’s modern screen heroine.
  • D. Maureen O'Sullivan
    Maureen O'Sullivan was an Irish-American actress best known for playing Jane opposite Johnny Weissmuller in the classic Tarzan film series of the 1930s and 1940s.
  • E. Clara Bow
    Clara Bow was a hugely popular American silent film actress of the 1920s, famously known as the original "It Girl" and a defining sex symbol of the Jazz Age.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770e9a89081908979efd1d9e6af66 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23c3c885081908edcece772b2e759 completed April 17, 2026, 1:57 p.m.
Created at: April 8, 2026, 9:23 p.m.