Triple

T15595544
Position Surface form Disambiguated ID Type / Status
Subject Sylvie Vartan E374883 entity
Predicate birthName P65 FINISHED
Object Sylvie Georges Vartan E374883 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: Sylvie Georges Vartan | Statement: [Sylvie Vartan, birthName, Sylvie Georges Vartan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sylvie Georges Vartan
Context triple: [Sylvie Vartan, birthName, Sylvie Georges 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. Eva Khatchadourian
    Eva Khatchadourian is the introspective, guilt-ridden mother and narrator in Lionel Shriver’s novel "We Need to Talk About Kevin," grappling with the aftermath of her son’s horrific violence.
  • C. Yvette Giraud
    Yvette Giraud was a French traditional pop singer known for her romantic chansons and popularity in both France and Japan in the mid-20th century.
  • D. Tedi Sarafian
    Tedi Sarafian is an American screenwriter and film producer best known for his work on major action and science fiction films.
  • E. Geneviève Brunet
    Geneviève Brunet is an actress known for her role in the visually distinctive French fantasy film "The City of Lost Children."
  • 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_69d85cce25008190b13b52745fbd719b completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e5f9db8819083abf80f01f32b3d completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f355ff48190a2c2c262c09e6de0 completed May 9, 2026, 4:22 p.m.
Created at: April 10, 2026, 4:12 a.m.