Triple

T21843220
Position Surface form Disambiguated ID Type / Status
Subject 67th Academy Awards E539305 entity
Predicate bestSupportingActressWinner P8119 FINISHED
Object Dianne Wiest 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: Dianne Wiest | Statement: [67th Academy Awards, bestSupportingActressWinner, Dianne Wiest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dianne Wiest
Context triple: [67th Academy Awards, bestSupportingActressWinner, Dianne Wiest]
  • A. Dianne Wiest chosen
    Dianne Wiest is an acclaimed American actress known for her versatile performances in film, television, and theater, including multiple award-winning supporting roles.
  • B. Jessica Walter
    Jessica Walter was an American actress best known for her sharp, comedic portrayal of Lucille Bluth on the television series "Arrested Development."
  • C. Shirley Heath
    Shirley Heath is a large open heathland and recreational green space located in the Shirley area of the West Midlands, England.
  • D. Stockard Channing
    Stockard Channing is an American actress best known for her roles as Rizzo in the film "Grease" and First Lady Abbey Bartlet on the television series "The West Wing."
  • E. Linda Purl
    Linda Purl is an American actress and singer best known for her roles on television series such as "Happy Days," "Matlock," and "The Office."
  • 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_69e0c476c3c88190a92d08ebb59a128a completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f0a7ad76d48190a1905cfdbe866323 completed April 28, 2026, 12:27 p.m.
Created at: April 16, 2026, 6:55 p.m.