Triple

T22233662
Position Surface form Disambiguated ID Type / Status
Subject Chocolat E549530 entity
Predicate stars P1956 FINISHED
Object Olivier Gourmet 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: Olivier Gourmet | Statement: [Chocolat, stars, Olivier Gourmet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Olivier Gourmet
Context triple: [Chocolat, stars, Olivier Gourmet]
  • A. Olivier Gourmet chosen
    Olivier Gourmet is a Belgian actor acclaimed for his collaborations with the Dardenne brothers and his award-winning performances in European art-house cinema.
  • B. Olivier Occéan
    Olivier Occéan is a retired Canadian professional soccer striker best known for his prolific club career in Europe and his appearances for the Canadian national team.
  • C. Daniel Boulud
    Daniel Boulud is a renowned French chef and restaurateur best known for his Michelin-starred restaurants, including the flagship Daniel in New York City.
  • D. Alain Chamfort
    Alain Chamfort is a French singer, songwriter, and composer known for his sophisticated pop music and long-standing presence in the French music scene since the 1970s.
  • E. Jean-Pierre Meyer
    Jean-Pierre Meyer is a French mathematician known for being a member of the influential collective pseudonym Nicolas Bourbaki.
  • 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_69e11e4102b881909cf47d3768e25c19 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12bf61504819093e70bee4c575d1c completed April 28, 2026, 9:51 p.m.
Created at: April 16, 2026, 8:38 p.m.