Triple

T7235069
Position Surface form Disambiguated ID Type / Status
Subject Marianne Peretti E155201 entity
Predicate name P16 FINISHED
Object Marianne Peretti E155201 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: Marianne Peretti | Statement: [Marianne Peretti, name, Marianne Peretti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marianne Peretti
Context triple: [Marianne Peretti, name, Marianne Peretti]
  • A. Marianne Peretti chosen
    Marianne Peretti was a French-Brazilian artist renowned for her monumental stained-glass works in major Brazilian modernist buildings, including Oscar Niemeyer’s Cathedral of Brasília.
  • B. Françoise Rosay
    Françoise Rosay was a prominent French stage and film actress known for her powerful character roles in European cinema from the 1920s through the 1950s.
  • C. 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.
  • D. Suzanne Jolibois
    Suzanne Jolibois was the wife of French phenomenologist and philosopher Maurice Merleau-Ponty.
  • E. Monique Dunan
    Monique Dunan was a costume designer known for her work on the film "Fedora."
  • 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_69c688143bfc81908d4176617735e601 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ea130e5c819087f74883760fe327 completed March 27, 2026, 8:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cc2d96588190bcf150cbfe4d015c completed March 28, 2026, 12:40 p.m.
Created at: March 27, 2026, 2:55 p.m.