Triple

T19504994
Position Surface form Disambiguated ID Type / Status
Subject But I'm a Cheerleader E487998 entity
Predicate stars P1956 FINISHED
Object Bud Cort 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: Bud Cort | Statement: [But I'm a Cheerleader, stars, Bud Cort]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bud Cort
Context triple: [But I'm a Cheerleader, stars, Bud Cort]
  • A. Bud Cort chosen
    Bud Cort is an American actor and director best known for his iconic role as the young Harold in the cult classic film "Harold and Maude."
  • B. Jack Elam
    Jack Elam was an American character actor best known for his distinctive lazy eye and memorable roles as villains and comic sidekicks in numerous Western films and television series.
  • C. Aldo Ray
    Aldo Ray was an American film actor known for his tough-guy roles and distinctive raspy voice in numerous Hollywood movies of the 1950s and 1960s.
  • D. Vic Tayback
    Vic Tayback was an American actor best known for his Emmy-nominated role as the gruff but lovable diner owner Mel Sharples in the film and television versions of "Alice."
  • E. Biagio Anthony Gazzarra
    Biagio Anthony Gazzarra, better known as Ben Gazzara, was an American actor renowned for his intense performances in film, television, and theater, particularly in the mid-20th century.
  • 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.