Triple

T7714310
Position Surface form Disambiguated ID Type / Status
Subject Heat (1995 film) E174842 entity
Predicate stars P1956 FINISHED
Object Ashley Judd E668094 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: Ashley Judd | Statement: [Heat (1995 film), stars, Ashley Judd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ashley Judd
Context triple: [Heat (1995 film), stars, Ashley Judd]
  • A. Ashley Judd chosen
    Ashley Judd is an American actress known for her roles in 1990s and 2000s thrillers and dramas, as well as for her prominent humanitarian and political activism.
  • 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. Elizabeth Berkley
    Elizabeth Berkley is an American actress best known for her roles in the TV series "Saved by the Bell" and the film "Showgirls."
  • D. Laura Kugler
    Laura Kugler was the wife of Victor Kugler, one of the helpers who hid Anne Frank and her family during World War II.
  • E. 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."
  • 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_69c6995c463c8190a14458036249d419 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c702ca8f048190a6ea27b8cee2f93e completed March 27, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8be2831788190a8ba7340b5d4d439 completed March 29, 2026, 5:52 a.m.
Created at: March 27, 2026, 4:04 p.m.