Triple

T19328277
Position Surface form Disambiguated ID Type / Status
Subject Puzzle (2018 film) E483416 entity
Predicate starring P1507 FINISHED
Object David Denman 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: David Denman | Statement: [Puzzle (2018 film), starring, David Denman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Denman
Context triple: [Puzzle (2018 film), starring, David Denman]
  • A. David Denman chosen
    David Denman is an American actor best known for his role as Roy Anderson on the U.S. version of "The Office" and for supporting performances in films and television series across comedy and drama.
  • B. David Denny
    David Denny was a 19th-century American pioneer and early settler of Seattle, Washington, who played a key role in the city's founding and development.
  • C. Dave Dennison
    Dave Dennison is a fictional character associated with Dani Dennison in the Hocus Pocus film universe, depicted as a member of her family.
  • D. 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."
  • E. Jeff Danna
    Jeff Danna is a Canadian film composer known for his scores for movies such as The Boondock Saints and various animated and dramatic films.
  • 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_69d8e8d13e3c81909d91d1d5ec37c095 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e6163f32f48190be17cccf4e537372 completed April 20, 2026, 12:04 p.m.
Created at: April 10, 2026, 1:33 p.m.