Triple

T20006783
Position Surface form Disambiguated ID Type / Status
Subject Electric Dreams E494479 entity
Predicate hasCastMember P2308 FINISHED
Object Vera Farmiga 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: Vera Farmiga | Statement: [Electric Dreams, hasCastMember, Vera Farmiga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vera Farmiga
Context triple: [Electric Dreams, hasCastMember, Vera Farmiga]
  • A. Vera Farmiga chosen
    Vera Farmiga is an American actress known for her acclaimed performances in films such as "The Conjuring" series and "Up in the Air," as well as the TV series "Bates Motel."
  • B. Taissa Farmiga
    Taissa Farmiga is an American actress best known for her recurring roles in the horror anthology series "American Horror Story" and films such as "The Nun."
  • C. Lena Olin
    Lena Olin is a Swedish actress known for her acclaimed film and television roles, including performances in "The Unbearable Lightness of Being," "Enemies, A Love Story," and "Alias."
  • D. Maria Bello
    Maria Bello is an American actress known for her versatile roles in film and television, including performances in projects like "A History of Violence," "ER," and "NCIS."
  • E. Maura West
    Maura West is an American actress best known for her long-running, Emmy-winning work in daytime soap operas.
  • 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e661a648a88190853ee741edcf6ca2 completed April 20, 2026, 5:25 p.m.
Created at: April 11, 2026, 3:33 p.m.