Triple

T19504964
Position Surface form Disambiguated ID Type / Status
Subject But I'm a Cheerleader E487998 entity
Predicate editor P1954 FINISHED
Object Jamie Babbit NE NERFINISHED

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: Jamie Babbit | Statement: [But I'm a Cheerleader, editor, Jamie Babbit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jamie Babbit
Context triple: [But I'm a Cheerleader, editor, Jamie Babbit]
  • A. Jamie Babbit chosen
    Jamie Babbit is an American film and television director best known for her cult queer coming-of-age comedy "But I'm a Cheerleader" and extensive work across popular TV series.
  • B. David Brisbin
    David Brisbin is an American character actor known for his supporting roles in film and television, including appearances in projects like "Fear and Loathing in Las Vegas" and "Twin Peaks."
  • C. Rusty Baillie
    Rusty Baillie is a pioneering British rock climber and mountaineer known for making historic first ascents in the UK during the mid-20th century.
  • D. Jo Bennett
    Jo Bennett is a fictional corporate executive and former CEO of Sabre in the U.S. television series "The Office."
  • E. Kay Bawden
    Kay Bawden is a social worker and one of the central adult characters in J.K. Rowling’s novel "The Casual Vacancy," whose professional and personal struggles highlight the book’s themes of class, responsibility, and community conflict.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d9d1c88190b01cd78b8be49384 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e635113fdc819098ea0f738d01925c completed April 20, 2026, 2:15 p.m.
Created at: April 10, 2026, 1:40 p.m.