Triple

T21866493
Position Surface form Disambiguated ID Type / Status
Subject Three Coins in the Fountain E539895 entity
Predicate director P255 FINISHED
Object Jean Negulesco 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: Jean Negulesco | Statement: [Three Coins in the Fountain, director, Jean Negulesco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jean Negulesco
Context triple: [Three Coins in the Fountain, director, Jean Negulesco]
  • A. Jean Negulesco chosen
    Jean Negulesco was a Romanian-American film director and screenwriter best known for his stylish Hollywood dramas and romances from the 1940s and 1950s.
  • B. Gregory La Cava
    Gregory La Cava was an American film director best known for his sophisticated 1930s comedies and character-driven dramas in Hollywood’s Golden Age.
  • C. Louis Tamburino
    Louis Tamburino is a researcher known for co-authoring scholarly work with physicist Ezra Newman, likely in the field of general relativity or theoretical physics.
  • D. Robert Tomarkin
    Robert Tomarkin was the husband of Academy Award–winning American actress Dorothy Malone.
  • E. Ivan Goff
    Ivan Goff was an Australian-born screenwriter best known for his work in Hollywood film and television, including co-writing influential crime dramas and creating popular TV series.
  • 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_69e0c478f59081909d54302b57fc1ce3 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f0d63f2ec48190956a3e99d8f98b1f completed April 28, 2026, 3:46 p.m.
Created at: April 16, 2026, 6:56 p.m.