Triple

T19440005
Position Surface form Disambiguated ID Type / Status
Subject Rachel Ferrier E486324 entity
Predicate portrayedBy P1507 FINISHED
Object Dakota Fanning NE NERFINISHED

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: Dakota Fanning | Statement: [Rachel Ferrier, portrayedBy, Dakota Fanning]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dakota Fanning
Context triple: [Rachel Ferrier, portrayedBy, Dakota Fanning]
  • A. Dakota Fanning chosen
    Dakota Fanning is an American actress who rose to fame as a child star in films like "I Am Sam" and has since built a diverse career in both mainstream and independent cinema.
  • B. Elle Fanning
    Elle Fanning is an American actress known for her versatile performances in films such as "Super 8," "Maleficent," and "The Neon Demon," as well as the TV series "The Great."
  • C. Haley Bennett
    Haley Bennett is an American actress and singer known for her versatile performances in films such as "The Girl on the Train," "The Magnificent Seven," and "Swallow."
  • D. Dakota O'Donnell
    Dakota O'Donnell is one of the adopted children of American comedian, actress, and television personality Rosie O'Donnell.
  • E. Maggie Grace
    Maggie Grace is an American actress best known for her roles in the TV series "Lost" and the "Taken" film series.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d7ad488190a3373045029b0f3b completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63364371081908e899c2a47af4e5d completed April 20, 2026, 2:08 p.m.
Created at: April 10, 2026, 1:38 p.m.