Triple

T9340339
Position Surface form Disambiguated ID Type / Status
Subject 300: Rise of an Empire E224749 entity
Predicate castMember P1668 FINISHED
Object Eva Green E263424 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: Eva Green | Statement: [300: Rise of an Empire, castMember, Eva Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eva Green
Context triple: [300: Rise of an Empire, castMember, 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 (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_69ca84286fcc81909f6e7fd7a7e862a2 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4bae2e2481909effc2dc89a642c5 completed April 1, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0f3bad4388190ac53657027262a46 completed April 4, 2026, 11:19 a.m.
Created at: March 30, 2026, 7:40 p.m.