Triple

T22022236
Position Surface form Disambiguated ID Type / Status
Subject Promising Young Woman E543872 entity
Predicate castMember P1668 FINISHED
Object Alison Brie 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: Alison Brie | Statement: [Promising Young Woman, castMember, Alison Brie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alison Brie
Context triple: [Promising Young Woman, castMember, Alison Brie]
  • A. Alison Brie chosen
    Alison Brie is an American actress known for her roles in television series like "Community" and "Mad Men," as well as her voice work in animated films.
  • B. Natasha Lyonne
    Natasha Lyonne is an American actress, writer, and director known for her distinctive raspy voice and roles in projects like Russian Doll, the American Pie films, and various acclaimed independent movies.
  • C. Ellie Kemper
    Ellie Kemper is an American actress and comedian best known for her roles in the sitcoms "The Office" and "Unbreakable Kimmy Schmidt."
  • D. S.E. Cupp
    S.E. Cupp is an American conservative political commentator, author, and television host known for her work on cable news and political debate programs.
  • E. Maya Erskine
    Maya Erskine is an American actress, writer, and comedian best known for co-creating and starring in the cringe-comedy series "PEN15."
  • 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_69e11e2e8ea4819084210fe06d3a1b8d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127c8ac6881909a9e96e0873a3ae2 completed April 28, 2026, 9:34 p.m.
Created at: April 16, 2026, 8:23 p.m.