Triple

T5743461
Position Surface form Disambiguated ID Type / Status
Subject Winston E126669 entity
Predicate supportsCharacter P16523 FINISHED
Object Rose Lorkowski E217548 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: Rose Lorkowski | Statement: [Winston, supportsCharacter, Rose Lorkowski]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rose Lorkowski
Context triple: [Winston, supportsCharacter, 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. Loralee Czuchna
    Loralee Czuchna is best known as the second wife of American actor and comedian Don Knotts.
  • C. Lisa Eilbacher
    Lisa Eilbacher is an American actress best known for her roles in 1980s films and television series, including prominent appearances in action and drama movies.
  • D. Anna Nolin
    Anna Nolin is an American educator and school district leader who serves as superintendent of the Newton Public Schools in Massachusetts.
  • E. Lisa Lassek
    Lisa Lassek is an American film and television editor known for her frequent collaborations with Joss Whedon on projects such as major Marvel superhero films and cult TV series.
  • 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_69c0083179548190b384b0bf3c08ca4d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02586b25c819083c409ce324268cc completed March 22, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c097f9b6e08190bb68ea850ba813ff completed March 23, 2026, 1:31 a.m.
Created at: March 22, 2026, 3:48 p.m.