Triple

T17810771
Position Surface form Disambiguated ID Type / Status
Subject Bille Brown E444695 entity
Predicate name P16 FINISHED
Object Bille Brown 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: Bille Brown | Statement: [Bille Brown, name, Bille Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bille Brown
Context triple: [Bille Brown, name, Bille Brown]
  • A. Bille Brown chosen
    Bille Brown was an Australian actor and playwright known for his work in theatre, film, and television, including roles in international productions.
  • B. Lou Brown
    Lou Brown is the gruff, no-nonsense manager of the Cleveland Indians baseball team in the comedy film "Major League."
  • C. Kay Hilliard
    Kay Hilliard is the central female protagonist in the 1956 musical film "The Opposite Sex," navigating love, betrayal, and personal growth within the world of high society marriages.
  • D. Steve Hilliard
    Steve Hilliard is a character in the romantic comedy film "The Opposite Sex."
  • E. Arvin Brown
    Arvin Brown is an American theatre and television director best known for his long tenure leading and shaping the artistic vision of New Haven’s Long Wharf Theatre.
  • 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_69d8b9f0de78819099395b14db75a8a6 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4887a50488190b9c148146ec607e6 completed April 19, 2026, 7:47 a.m.
Created at: April 10, 2026, 10:14 a.m.