Triple

T5188517
Position Surface form Disambiguated ID Type / Status
Subject The Rainmaker E117089 entity
Predicate portrayedBy P1507 FINISHED
Object Virginia Madsen E415997 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: Virginia Madsen | Statement: [The Rainmaker, portrayedBy, Virginia Madsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Virginia Madsen
Context triple: [The Rainmaker, portrayedBy, Virginia Madsen]
  • A. Virginia Madsen chosen
    Virginia Madsen is an American actress known for her versatile film and television roles, including acclaimed performances in movies such as "Sideways" and "Candyman."
  • B. Samantha Morton
    Samantha Morton is an acclaimed English actress and director known for her intense, emotionally rich performances in independent films and major productions alike.
  • C. Téa Leoni
    Téa Leoni is an American actress and producer best known for her leading roles in film and television, including the political drama series "Madam Secretary."
  • D. Jorja Fox
    Jorja Fox is an American actress best known for her long-running role as Sara Sidle on the television series CSI: Crime Scene Investigation.
  • E. 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."
  • 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_69bd44620ff48190bcac01782107a397 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd79c56280819085926316f7b520bc completed March 20, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69bee08af954819080dbe7ea1ac6ddb0 completed March 21, 2026, 6:16 p.m.
Created at: March 20, 2026, 1:46 p.m.