Triple

T4584342
Position Surface form Disambiguated ID Type / Status
Subject Pennebaker Hegedus Films E101931 entity
Predicate associatedWith P37 FINISHED
Object Chris Hegedus E454614 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: Chris Hegedus | Statement: [Pennebaker Hegedus Films, associatedWith, Chris Hegedus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chris Hegedus
Context triple: [Pennebaker Hegedus Films, associatedWith, Chris Hegedus]
  • A. Chris Hegedus chosen
    Chris Hegedus is an American documentary filmmaker known for her long-time collaboration with D. A. Pennebaker on influential cinéma vérité films.
  • B. Vern Sneider
    Vern Sneider was an American novelist best known for his humorous and satirical depictions of post–World War II American military occupation and cross-cultural encounters.
  • C. Paul Hirsch
    Paul Hirsch is an American film editor renowned for his work on major Hollywood films, including the original Star Wars.
  • D. Michael P. Steinberg
    Michael P. Steinberg is an American historian and musicologist known for his scholarship on German cultural and intellectual history and his leadership roles in higher education.
  • E. Bud Yorkin
    Bud Yorkin was an American television producer and director best known for his influential work in 1970s sitcoms that helped redefine socially conscious TV comedy.
  • 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_69bd43d4ce208190b53158c882b222e3 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd590411dc81909c55d1c42a4d44ef completed March 20, 2026, 2:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69be102049d481908743d66f76905c69 completed March 21, 2026, 3:27 a.m.
Created at: March 20, 2026, 1:10 p.m.