Triple

T22234221
Position Surface form Disambiguated ID Type / Status
Subject Ellen Page E549545 entity
Predicate portrayedCharacter P1668 FINISHED
Object Juno MacGuff 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: Juno MacGuff | Statement: [Ellen Page, portrayedCharacter, Juno MacGuff]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Juno MacGuff
Context triple: [Ellen Page, portrayedCharacter, Juno MacGuff]
  • A. Juno MacGuff chosen
    Juno MacGuff is the witty, independent, and unexpectedly pregnant teenage protagonist of the 2007 film "Juno," known for her sharp dialogue and emotional maturity.
  • B. Juno Wright
    Juno Wright is a child of British actress and singer Carmen Ejogo.
  • C. Juno Boyle
    Juno Boyle is the resilient, long-suffering matriarch in Seán O’Casey’s play "Juno and the Paycock," embodying strength and practicality amid family and political turmoil in Dublin.
  • D. Leslie
    Leslie is the middle name of early 20th-century Major League Baseball pitcher Hippo Vaughn, a standout left-hander best known for his time with the Chicago Cubs.
  • E. Leslie
    Leslie is a Toronto subway station on Line 4 Sheppard in the city's transit system.
  • 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_69e11e4102b881909cf47d3768e25c19 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12bf61504819093e70bee4c575d1c completed April 28, 2026, 9:51 p.m.
Created at: April 16, 2026, 8:38 p.m.