Triple

T5683180
Position Surface form Disambiguated ID Type / Status
Subject Three Coins in the Fountain E125245 entity
Predicate stars P1956 FINISHED
Object Louis Jourdan E255079 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: Louis Jourdan | Statement: [Three Coins in the Fountain, stars, 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, stars, 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. 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.
  • C. Jean Marais
    Jean Marais was a renowned French actor, director, and sculptor best known for his collaborations with filmmaker Jean Cocteau and his roles in classic French cinema.
  • D. Jacques Balsan
    Jacques Balsan was a French aviation pioneer, industrialist, and socialite known for his early involvement in ballooning and powered flight as well as his marriage into the prominent Vanderbilt family.
  • E. Jean Gabin
    Jean Gabin was a legendary French film actor renowned for his roles in classic 1930s–1960s cinema and as an icon of poetic realism.
  • 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_69c0082a884c8190a79001bae658941f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023b780248190a912d2dddbd0aa17 completed March 22, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a39756c819098b06911c58d50a8 completed March 22, 2026, 9:08 p.m.
Created at: March 22, 2026, 3:44 p.m.