Triple

T9433725
Position Surface form Disambiguated ID Type / Status
Subject Thelma Evans E227448 entity
Predicate portrayedBy P1507 FINISHED
Object BernNadette Stanis E161505 NE FINISHED

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: BernNadette Stanis | Statement: [Thelma Evans, portrayedBy, BernNadette Stanis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BernNadette Stanis
Context triple: [Thelma Evans, portrayedBy, BernNadette Stanis]
  • A. BernNadette Stanis chosen
    BernNadette Stanis is an American actress best known for playing Thelma Evans on the classic 1970s sitcom "Good Times."
  • B. Jennifer Coolidge
    Jennifer Coolidge is an American actress and comedian best known for her scene-stealing roles in films like "Legally Blonde" and the "American Pie" series, as well as the TV series "The White Lotus."
  • C. Kathie Moffat
    Kathie Moffat is the seductive and treacherous femme fatale in the classic 1947 film noir "Out of the Past."
  • D. Susan Cummings
    Susan Cummings was a German-American film and television actress active in the 1950s and 1960s, known for her roles in adventure and genre pictures as well as numerous TV guest appearances.
  • E. Kate Dickie
    Kate Dickie is a Scottish actress known for her intense and often unsettling performances in film and television, including roles in projects like "Red Road," "Game of Thrones," and "The Witch."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca8437a7ac81908651de48f2d2141d completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd7e62d53c81908055e0967e6cd54d completed April 1, 2026, 8:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1104514d481908d7cb9a87a01f1e2 completed April 4, 2026, 1:21 p.m.
Created at: March 30, 2026, 7:49 p.m.