Triple

T2825881
Position Surface form Disambiguated ID Type / Status
Subject The Bodyguard E54919 entity
Predicate editor P1954 FINISHED
Object Don Brochu E54919 NE FINISHED

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: Don Brochu | Statement: [The Bodyguard, editor, Don Brochu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Don Brochu
Context triple: [The Bodyguard, editor, Don Brochu]
  • A. Don Brochu chosen
    Don Brochu is a film editor best known for his work on major Hollywood movies, including the hit thriller "The Bodyguard."
  • B. Frank Bracht
    Frank Bracht was an American film editor known for his work on mid-20th-century Hollywood productions, including the biographical drama "Harlow" (1965).
  • C. David Bonderman
    David Bonderman is an American billionaire businessman and private equity investor, best known as a founding partner of TPG Capital and as a prominent owner of major professional sports franchises.
  • D. Winston Hibler
    Winston Hibler was an American screenwriter, producer, and narrator best known for his long association with Walt Disney Studios, where he contributed to classic animated features and nature documentaries.
  • E. Edwin Blashfield
    Edwin Blashfield was an American muralist and painter best known for his large-scale allegorical works in prominent public buildings across the United States.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ab49e100c0819082a40cb797383243 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde925e688190bb390d3182f8c4f0 completed March 7, 2026, 8:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc4b8f688190827dfedda7a55828 completed March 11, 2026, 5:23 a.m.
Created at: March 6, 2026, 9:59 p.m.