Triple

T4198115
Position Surface form Disambiguated ID Type / Status
Subject 6 Underground E86001 entity
Predicate starring P1507 FINISHED
Object Mélanie Laurent E313986 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: Mélanie Laurent | Statement: [6 Underground, starring, Mélanie Laurent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mélanie Laurent
Context triple: [6 Underground, starring, Mélanie Laurent]
  • A. Mélanie Laurent chosen
    Mélanie Laurent is a French actress, director, and singer best known internationally for her acclaimed role in Quentin Tarantino’s film "Inglourious Basterds."
  • B. 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.
  • C. Mia Wasikowska
    Mia Wasikowska is an Australian actress known for her versatile performances in films such as "Alice in Wonderland," "Jane Eyre," and various independent dramas.
  • D. Rooney Mara
    Rooney Mara is an American actress known for her acclaimed performances in films such as "The Girl with the Dragon Tattoo" and "Carol."
  • 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_69aed93b89f48190a31f6d57c760e42f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0360bc8081908ceb2483eef89174 completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b58a12c11481908033229ecf90c9f9 completed March 14, 2026, 4:17 p.m.
Created at: March 9, 2026, 3:48 p.m.