Triple

T8576206
Position Surface form Disambiguated ID Type / Status
Subject Marguerite de Carrouges E203053 entity
Predicate portrayedBy P1507 FINISHED
Object Jodie Comer E66953 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: Jodie Comer | Statement: [Marguerite de Carrouges, portrayedBy, Jodie Comer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jodie Comer
Context triple: [Marguerite de Carrouges, portrayedBy, Jodie Comer]
  • A. Jodie Comer chosen
    Jodie Comer is an English actress best known for her critically acclaimed, chameleonic performance as assassin Villanelle in the television series "Killing Eve."
  • B. Vanessa Kirby
    Vanessa Kirby is an English actress known for her acclaimed performances in both film and television, including her breakout role as Princess Margaret in the Netflix series "The Crown."
  • C. Emma Corrin
    Emma Corrin is an English actor best known for their acclaimed portrayal of Princess Diana in the television series "The Crown."
  • D. Tamsin Egerton
    Tamsin Egerton is an English actress and model known for roles in films such as "St Trinian's," "Keeping Mum," and "The Look of Love."
  • E. Maria Riva
    Maria Riva is a German-American actress and author best known as the daughter and biographer of film legend Marlene Dietrich.
  • 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_69ca8328ebe481909a8c038fa79959b4 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbea9638c081909a537cc44e485bee completed March 31, 2026, 3:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce899dd7d48190b44338b92ad68bd0 completed April 2, 2026, 3:22 p.m.
Created at: March 30, 2026, 6:21 p.m.