Triple

T17490210
Position Surface form Disambiguated ID Type / Status
Subject Johnny Hallyday E425883 entity
Predicate spouse P13 FINISHED
Object Sylvie Vartan 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: Sylvie Vartan | Statement: [Johnny Hallyday, spouse, Sylvie Vartan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sylvie Vartan
Context triple: [Johnny Hallyday, spouse, Sylvie Vartan]
  • A. Sylvie Vartan chosen
    Sylvie Vartan is a Bulgarian-born French pop singer and actress who became one of France’s most popular yé-yé idols in the 1960s.
  • B. Leila Roker
    Leila Roker is an American media personality and journalist known as the daughter of longtime television weather anchor and host Al Roker.
  • C. Françoise Brion
    Françoise Brion is a French actress known for her work in European cinema from the 1960s onward, including collaborations with prominent auteurs.
  • D. Mireille Soria
    Mireille Soria is a film producer best known for her work on major animated features at DreamWorks Animation.
  • E. Claudine Longet
    Claudine Longet is a French-born singer and actress known for her soft, breathy vocal style and appearances in 1960s American television and film.
  • 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_69d889dccf7481909264a1844a2e9100 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451d519488190a08da1b529c08445 completed April 19, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:48 a.m.