Triple

T20880692
Position Surface form Disambiguated ID Type / Status
Subject Roger Waters E514136 entity
Predicate spouse P13 FINISHED
Object Laurie Durning 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: Laurie Durning | Statement: [Roger Waters, spouse, Laurie Durning]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laurie Durning
Context triple: [Roger Waters, spouse, Laurie Durning]
  • A. Laurie Durning chosen
    Laurie Durning is an American filmmaker and costume designer best known for her long-term relationship and later marriage to Pink Floyd co-founder Roger Waters.
  • B. Deborah Rush
    Deborah Rush is an American actress known for her character roles in film, television, and theater, including appearances in comedies and independent productions.
  • C. Tyne Daly
    Tyne Daly is an American actress acclaimed for her powerful performances in television dramas, film, and theater, including her iconic role in the series "Cagney & Lacey."
  • D. Lucinda Jenney
    Lucinda Jenney is an American character actress known for her versatile supporting roles in films and television since the 1980s.
  • E. Patty Considine
    Patty Considine is an English actor, director, and screenwriter known for his intense, character-driven performances in films such as "Dead Man's Shoes," "In America," and "Hot Fuzz."
  • 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_69e0b4f733f081908a401c0b7beb0b9f completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c67974348190bd3484032c0d7b31 completed April 21, 2026, 12:36 a.m.
Created at: April 16, 2026, 12:46 p.m.