Triple

T12877416
Position Surface form Disambiguated ID Type / Status
Subject Red Heat E308003 entity
Predicate castMember P1668 FINISHED
Object Gina Gershon E59417 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: Gina Gershon | Statement: [Red Heat, castMember, Gina Gershon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gina Gershon
Context triple: [Red Heat, castMember, Gina Gershon]
  • A. Gina Gershon chosen
    Gina Gershon is an American actress known for her versatile roles in film, television, and theater, including standout performances in movies like "Bound" and "Showgirls."
  • B. 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."
  • C. Jennifer Tilly
    Jennifer Tilly is an American actress and poker player known for her distinctive voice and roles in films such as "Bullets Over Broadway" and the "Child's Play" horror franchise.
  • D. Annabella Sciorra
    Annabella Sciorra is an American actress known for her work in film and television, including acclaimed roles in movies like "Jungle Fever" and the TV series "The Sopranos."
  • E. Virginia Madsen
    Virginia Madsen is an American actress known for her versatile film and television roles, including acclaimed performances in movies such as "Sideways" and "Candyman."
  • 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970fa8474819086a8af3c90f3ca84 completed April 10, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7265af6cc81908837c80797a8e704 completed May 3, 2026, 10:41 a.m.
Created at: April 9, 2026, 5:38 p.m.