Triple

T18220925
Position Surface form Disambiguated ID Type / Status
Subject Dan Fielding E436300 entity
Predicate associatedWithCharacter P1481 FINISHED
Object Roz Russell 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: Roz Russell | Statement: [Dan Fielding, associatedWithCharacter, Roz Russell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roz Russell
Context triple: [Dan Fielding, associatedWithCharacter, Roz Russell]
  • A. Roz Russell chosen
    Roz Russell is a tough, no-nonsense bailiff character from the sitcom "Night Court," known for her deadpan humor and intimidating presence.
  • B. Rosalind Russell
    Rosalind Russell was an acclaimed American actress best known for her sharp-witted performances in screwball comedies and strong, independent female roles on stage and screen.
  • C. Dorothy Winters
    Dorothy Winters is a central character in the 1996 romantic fantasy film "Michael," portrayed as a young woman whose life is profoundly affected by her encounter with the archangel Michael.
  • D. Sharon Reed
    Sharon Reed is a visual effects industry professional best known as one of the founders of the renowned VFX and creative studio Framestore.
  • E. Nancy Richardson
    Nancy Richardson is a film editor known for her work on notable movies including the drama "To Sleep with Anger."
  • 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_69d8b9103a8081908bbb0836fef10efd completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e47b5bfc819085c5935c08361ba9 completed April 19, 2026, 2:19 p.m.
Created at: April 10, 2026, 10:32 a.m.