Triple

T21866516
Position Surface form Disambiguated ID Type / Status
Subject Three Coins in the Fountain E539895 entity
Predicate starring P1507 FINISHED
Object Louis Jourdan 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: Louis Jourdan | Statement: [Three Coins in the Fountain, starring, Louis Jourdan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Louis Jourdan
Context triple: [Three Coins in the Fountain, starring, Louis Jourdan]
  • A. Louis Jourdan chosen
    Louis Jourdan was a French film and television actor best known for his suave, sophisticated roles in Hollywood productions such as "Gigi" and "Octopussy."
  • B. Claude Brasseur
    Claude Brasseur was a prominent French actor known for his versatile performances in film, television, and theater, and as part of a celebrated family of French performers.
  • C. Joseph Noiret
    Joseph Noiret was a Belgian poet, painter, and art critic best known as a founding figure of the postwar avant-garde COBRA movement.
  • D. Michel Galabru
    Michel Galabru was a prolific French actor and comedian known for his numerous roles in film, television, and theater, often portraying gruff yet humorous characters.
  • E. Laurent Dailland
    Laurent Dailland is a French cinematographer known for his work on numerous feature films, including the drama "Il y a longtemps que je t’aime."
  • 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.