Triple

T23492094
Position Surface form Disambiguated ID Type / Status
Subject Too Many Girls E570702 entity
Predicate screenwriter P2831 FINISHED
Object John Twist 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: John Twist | Statement: [Too Many Girls, screenwriter, John Twist]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Twist
Context triple: [Too Many Girls, screenwriter, John Twist]
  • A. John Twist chosen
    John Twist was an American screenwriter active during Hollywood's mid-20th century studio era, contributing scripts to numerous feature films.
  • B. John Twist
    John Twist is the formal given name of the fictional character Jack Twist from Annie Proulx’s short story and the film adaptation "Brokeback Mountain."
  • C. Bartholomew Green
    Bartholomew Green was a prominent early 18th-century Boston printer and publisher known for producing influential colonial American works.
  • D. Henry Burden
    Henry Burden was a 19th-century Scottish-American industrialist and inventor known for revolutionizing iron manufacturing, particularly through his patented horseshoe machine and development of the Burden Iron Works in Troy, New York.
  • E. Oliver Braddick
    Oliver Braddick is a British experimental psychologist and neuroscientist known for his influential work on visual perception and development.
  • 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_69e245b0b01481908f636939bedd804c completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a7dd56408190b459077e433ed1c3 completed April 29, 2026, 6:40 a.m.
Created at: April 17, 2026, 6:05 p.m.