Triple

T22274145
Position Surface form Disambiguated ID Type / Status
Subject Cours Simon E550556 entity
Predicate hasNotableAlumni P51 FINISHED
Object Eva Green 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: Eva Green | Statement: [Cours Simon, hasNotableAlumni, Eva Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eva Green
Context triple: [Cours Simon, hasNotableAlumni, Eva Green]
  • A. Eva Green chosen
    Eva Green is a French actress known for her dark, intense performances in film and television, including prominent roles in projects like "Casino Royale" and "Penny Dreadful."
  • B. Isabelle Carré
    Isabelle Carré is a French actress known for her performances in films such as "Se souvenir des belles choses," for which she won the César Award for Best Actress.
  • C. Carmen Ejogo
    Carmen Ejogo is a British actress and singer known for her versatile film and television roles, including her acclaimed portrayal of Coretta Scott King in the historical drama "Selma."
  • D. Gemma Arterton
    Gemma Arterton is an English actress known for her roles in films such as "St Trinian's," "Quantum of Solace," and "Prince of Persia: The Sands of Time."
  • E. Bérénice Marlohe
    Bérénice Marlohe is a French actress best known internationally for her role as Sévérine in the James Bond film "Skyfall."
  • 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_69e11e43d8208190aff4f9cf7f2c2a8a completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f14ea547e4819098baf88f3c605242 completed April 29, 2026, 12:19 a.m.
Created at: April 16, 2026, 8:40 p.m.