Triple

T18731373
Position Surface form Disambiguated ID Type / Status
Subject Sunshine Cleaning E458041 entity
Predicate character P662 FINISHED
Object Rose Lorkowski 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: Rose Lorkowski | Statement: [Sunshine Cleaning, character, Rose Lorkowski]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rose Lorkowski
Context triple: [Sunshine Cleaning, character, Rose Lorkowski]
  • A. Rose Lorkowski chosen
    Rose Lorkowski is the struggling single mother and former high school cheerleader who starts a crime-scene cleanup business in the film "Sunshine Cleaning."
  • B. Liz Cackowski
    Liz Cackowski is an American comedy writer and actress known for her work on shows like Saturday Night Live and various film and television projects.
  • C. Lorie Lassner
    Lorie Lassner is known as the wife of television producer and longtime Ellen DeGeneres Show executive producer Andy Lassner.
  • D. Loralee Czuchna
    Loralee Czuchna is best known as the second wife of American actor and comedian Don Knotts.
  • E. Carol Laise
    Carol Laise was an American diplomat and educator who notably served as U.S. Ambassador to Nepal and later held senior positions in the U.S. State Department.
  • 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_69d8d393ba9c8190a8b03b04ddbb0a09 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e56d7854748190b66c4aaadfd67f29 completed April 20, 2026, 12:04 a.m.
Created at: April 10, 2026, 11:51 a.m.