Triple

T20141095
Position Surface form Disambiguated ID Type / Status
Subject Things Heard & Seen E491165 entity
Predicate screenwriter P2831 FINISHED
Object Elizabeth Brundage 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: Elizabeth Brundage | Statement: [Things Heard & Seen, screenwriter, Elizabeth Brundage]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elizabeth Brundage
Context triple: [Things Heard & Seen, screenwriter, Elizabeth Brundage]
  • A. Elizabeth Brundage chosen
    Elizabeth Brundage is an American novelist known for her psychologically rich literary thrillers that often blend domestic drama with elements of crime and the supernatural.
  • B. Margaret Brundage
    Margaret Brundage was an American illustrator best known for her sensual, atmospheric fantasy and horror cover paintings for pulp magazines in the 1930s.
  • C. Laura Bickford
    Laura Bickford is an American film producer best known for her work on acclaimed independent and studio films, including the Oscar-winning drama "Traffic."
  • D. Annmarie Fulton
    Annmarie Fulton is an actress best known for her role in the film "Sweet Sixteen."
  • E. Elizabeth Reaser
    Elizabeth Reaser is an American actress best known for her roles in the Twilight film series and the television drama Grey's Anatomy.
  • 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_69da6265f8f0819080b29c752a574088 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6679b179c8190a9511df8ed82098a completed April 20, 2026, 5:51 p.m.
Created at: April 11, 2026, 11:32 p.m.