Triple

T10750971
Position Surface form Disambiguated ID Type / Status
Subject Bug (2006 film) E253569 entity
Predicate starring P1507 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: [Bug (2006 film), starring, Ashley Judd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ashley Judd
Context triple: [Bug (2006 film), starring, 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. Allison Hunt
    Allison Hunt is a fictional character in the television series "Grey's Anatomy," known primarily as the deceased sister of trauma surgeon Owen Hunt, whose death deeply affects his storyline.
  • 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d71dc0ad188190b747bf9d10cf5de5 completed April 9, 2026, 3:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69de84a63de0819085f1e982c8348811 completed April 14, 2026, 6:17 p.m.
Created at: April 8, 2026, 9:15 p.m.