Triple

T19593289
Position Surface form Disambiguated ID Type / Status
Subject The Water Diviner E470288 entity
Predicate notableCastMember P7010 FINISHED
Object Olga Kurylenko 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: Olga Kurylenko | Statement: [The Water Diviner, notableCastMember, Olga Kurylenko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Olga Kurylenko
Context triple: [The Water Diviner, notableCastMember, Olga Kurylenko]
  • A. Olga Kurylenko chosen
    Olga Kurylenko is a Ukrainian-French actress and model best known for her roles in action and thriller films, including the James Bond movie "Quantum of Solace."
  • B. Svetlana Khodchenkova
    Svetlana Khodchenkova is a Russian film and television actress known internationally for roles in movies such as "Tinker Tailor Soldier Spy" and "The Wolverine."
  • C. Angelina Melnikova
    Angelina Melnikova is a Russian artistic gymnast and Olympic champion known for her success in team and individual all-around events at major international competitions.
  • D. Dominika Egorova
    Dominika Egorova is the fictional Russian ballerina-turned-spy protagonist of the espionage thriller "Red Sparrow."
  • E. Eva Green
    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."
  • 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_69d8e510024481908415c0d616fa6186 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e640782e2c8190b5baef07a2bdd015 completed April 20, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:43 p.m.