Triple

T9723331
Position Surface form Disambiguated ID Type / Status
Subject Evelyn Abbott E235536 entity
Predicate portrayedBy P1507 FINISHED
Object Emily Blunt E4055 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: Emily Blunt | Statement: [Evelyn Abbott, portrayedBy, Emily Blunt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emily Blunt
Context triple: [Evelyn Abbott, portrayedBy, Emily Blunt]
  • A. Emily Blunt chosen
    Emily Blunt is a British actress known for her versatile performances in films such as "The Devil Wears Prada," "Edge of Tomorrow," "A Quiet Place," and "Mary Poppins Returns."
  • B. Jessica Chastain
    Jessica Chastain is an acclaimed American actress known for her versatile performances in films such as "Zero Dark Thirty," "The Help," and "Molly's Game."
  • C. Gillian Murphy
    Gillian Murphy is a renowned American ballet dancer and longtime principal with American Ballet Theatre, celebrated for her powerful technique and dramatic artistry.
  • D. Keira Knightley
    Keira Knightley is an English actress known for her roles in period dramas and major film franchises such as "Pirates of the Caribbean" and "Pride & Prejudice."
  • E. Alicia Vikander
    Alicia Vikander is a Swedish actress known for her acclaimed performances in films such as "Ex Machina," "The Danish Girl," and "Tomb Raider."
  • 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_69ca84d0123c819096f9dc3b6abb0881 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9e75abd48190a6e6679ec51496e8 completed April 1, 2026, 10:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1afb089e48190a14ed0c0f81872c7 completed April 5, 2026, 12:41 a.m.
Created at: March 30, 2026, 8:20 p.m.