Triple

T1790932
Position Surface form Disambiguated ID Type / Status
Subject The Last Duel E39491 entity
Predicate leadActor 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: [The Last Duel, leadActor, Jodie Comer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jodie Comer
Context triple: [The Last Duel, leadActor, 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. 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."
  • D. Florence Pugh
    Florence Pugh is an English actress acclaimed for her emotionally intense and versatile performances in films such as "Lady Macbeth," "Midsommar," and "Little Women."
  • E. Anya Taylor-Joy
    Anya Taylor-Joy is an award-winning actress known for her breakout role in "The Queen's Gambit" and performances in films such as "The Witch," "Split," and "Last Night in Soho."
  • 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_69a88631854081909723959921e45c2b completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa6512804c8190a5743c10bd37f83f completed March 6, 2026, 5:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfb9c69488190abcbbf796176fca5 completed March 8, 2026, 10:43 p.m.
Created at: March 4, 2026, 7:32 p.m.