Triple

T11036682
Position Surface form Disambiguated ID Type / Status
Subject Queen of the Damned E260903 entity
Predicate editor P1954 FINISHED
Object Dany Cooper E859500 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: Dany Cooper | Statement: [Queen of the Damned, editor, Dany Cooper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dany Cooper
Context triple: [Queen of the Damned, editor, Dany Cooper]
  • A. Dany Cooper chosen
    Dany Cooper is an Australian film editor known for her work on numerous acclaimed feature films and television projects.
  • B. Andy Cooper
    Andy Cooper was an American Negro league baseball pitcher and later manager, renowned for his standout career in the 1920s and 1930s and his eventual induction into the Baseball Hall of Fame.
  • C. Kyle Cooper
    Kyle Cooper is a composer recognized for his award-winning work in video game music, including earning top honors at The Game Awards.
  • D. Kit Carruthers
    Kit Carruthers is the charismatic yet disturbingly detached young drifter and spree killer at the center of Terrence Malick’s film "Badlands."
  • E. Blaine Gibson
    Blaine Gibson was an American animator and sculptor best known for his long career at Disney, where he created many of the iconic Audio-Animatronic figures for Disneyland and other Disney parks.
  • 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_69d6aa979bdc8190bf0e79104cc098c1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797e9e3fc8190802195ac9fcb8e28 completed April 9, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3a9c669608190af97c461beaf9f31 completed April 18, 2026, 3:56 p.m.
Created at: April 8, 2026, 9:25 p.m.