Triple

T18093441
Position Surface form Disambiguated ID Type / Status
Subject Down by Law E433026 entity
Predicate castMember P1668 FINISHED
Object Vernel Bagneris 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: Vernel Bagneris | Statement: [Down by Law, castMember, Vernel Bagneris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vernel Bagneris
Context triple: [Down by Law, castMember, Vernel Bagneris]
  • A. Vernel Bagneris chosen
    Vernel Bagneris is an American actor, playwright, and director best known for his work in theater and film, particularly in jazz- and blues-themed productions.
  • B. Norbert Brodine
    Norbert Brodine was an American cinematographer known for his work on numerous Hollywood films from the silent era through the mid-20th century, particularly in film noir and crime dramas.
  • C. John Bagni
    John Bagni was an American actor and screenwriter active in mid-20th-century film and radio.
  • D. Marvin Natiss
    Marvin Natiss is an American local politician who has served as a leading municipal official in North Hills, New York.
  • E. Ralph Kabnis
    Ralph Kabnis is the troubled, introspective schoolteacher protagonist of Jean Toomer’s Cane, whose experiences in the Jim Crow South explore themes of racial identity, alienation, and spiritual crisis.
  • 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_69d8b907d05c819083cc3bd6021089e6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dd1a75048190924ebc01da83851b completed April 19, 2026, 1:48 p.m.
Created at: April 10, 2026, 10:27 a.m.