Triple

T20248514
Position Surface form Disambiguated ID Type / Status
Subject Sink E498487 entity
Predicate hasNotableBearer P458 FINISHED
Object Sadie Sink (actress) 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: Sadie Sink (actress) | Statement: [Sink, hasNotableBearer, Sadie Sink (actress)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sadie Sink (actress)
Context triple: [Sink, hasNotableBearer, Sadie Sink (actress)]
  • A. Sadie Sink chosen
    Sadie Sink is an American actress best known for her role as Max Mayfield on the Netflix science fiction-horror series "Stranger Things."
  • B. Sadie Benning
    Sadie Benning is an American video and visual artist and filmmaker known for their pioneering lo-fi PixelVision diary films and explorations of queer identity and youth.
  • C. Tracee Joy Silberstein
    Tracee Joy Silberstein is the birth name of Tracee Ellis Ross, an American actress and television host best known for her roles on the sitcoms "Girlfriends" and "Black-ish."
  • D. Kaitlyn Dever
    Kaitlyn Dever is an American actress known for her acclaimed performances in projects such as "Booksmart," "Short Term 12," and the miniseries "Unbelievable."
  • E. Samara Weaving
    Samara Weaving is an Australian actress known for her roles in film and television, particularly in horror-comedy and thriller projects such as "Ready or Not" and "The Babysitter."
  • 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_69da6274c58c81909c646eabed6f4f30 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e673a5ce4081908dff86ed4c613fd6 completed April 20, 2026, 6:42 p.m.
Created at: April 11, 2026, 11:41 p.m.