Triple

T10467249
Position Surface form Disambiguated ID Type / Status
Subject Kate & Leopold E246828 entity
Predicate editedBy P1954 FINISHED
Object David Brenner E236325 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: David Brenner | Statement: [Kate & Leopold, editedBy, David Brenner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Brenner
Context triple: [Kate & Leopold, editedBy, David Brenner]
  • A. David Brenner chosen
    David Brenner was an American film editor known for his work on major Hollywood blockbusters, including several of director Zack Snyder’s films.
  • B. Eric Brenner
    Eric Brenner is a film producer known for his work on independent movies, including the action drama "Mercury Plains."
  • C. Sean Brenner
    Sean Brenner is a character in the supernatural horror film "Insidious: Chapter 3," appearing as part of the story’s haunted family dynamic.
  • D. Phil Bronstein
    Phil Bronstein is an American journalist and editor best known for his long tenure at the San Francisco Chronicle and his marriage to actress Sharon Stone.
  • E. Larry Brezner
    Larry Brezner was an American film producer and talent manager known for producing popular comedies such as "Good Morning, Vietnam," "The 'Burbs," and "Ride Along."
  • 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_69d381c16c248190a2fe5b471e584e9c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5092e3230819098ab444f73c9bd40 completed April 7, 2026, 1:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69e215e3c3c88190833c1f56288629a2 completed April 17, 2026, 11:13 a.m.
Created at: April 6, 2026, 12:20 p.m.