Triple

T2385839
Position Surface form Disambiguated ID Type / Status
Subject Sofia Boutella E48820 entity
Predicate name P16 FINISHED
Object Sofia Boutella E48820 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: Sofia Boutella | Statement: [Sofia Boutella, name, Sofia Boutella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sofia Boutella
Context triple: [Sofia Boutella, name, Sofia Boutella]
  • A. Sofia Boutella chosen
    Sofia Boutella is an Algerian-French dancer and actress known for her dynamic action roles in films such as "Kingsman: The Secret Service," "Star Trek Beyond," and "The Mummy."
  • B. Bérénice Marlohe
    Bérénice Marlohe is a French actress best known internationally for her role as Sévérine in the James Bond film "Skyfall."
  • C. Lea Seydoux
    Léa Seydoux is a French actress known for her roles in films such as "Blue Is the Warmest Colour," multiple James Bond movies, and various international arthouse and blockbuster productions.
  • D. 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."
  • E. Elena Anaya
    Elena Anaya is a Spanish actress known for her roles in both European cinema and Hollywood productions, including prominent performances in films like "The Skin I Live In."
  • 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_69a88aa5f63081908d07fd302029fcbd completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc7d8a918819089a210e74e13be6e completed March 7, 2026, 6:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea8bae2ec8190962479832bf7762e completed March 9, 2026, 11:02 a.m.
Created at: March 4, 2026, 7:57 p.m.