Triple

T9984101
Position Surface form Disambiguated ID Type / Status
Subject Designated Survivor E196522 entity
Predicate creator P184 FINISHED
Object David Guggenheim E177059 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 Guggenheim | Statement: [Designated Survivor, creator, David Guggenheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Guggenheim
Context triple: [Designated Survivor, creator, David Guggenheim]
  • A. Davis Guggenheim chosen
    Davis Guggenheim is an American filmmaker and producer best known for directing influential documentaries such as "An Inconvenient Truth," "Waiting for 'Superman'," and "He Named Me Malala."
  • B. Paul Hirsch
    Paul Hirsch is an American film editor renowned for his work on major Hollywood films, including the original Star Wars.
  • C. Paul Hirsch
    Paul Hirsch was a German Social Democratic politician who briefly served as Minister President of Prussia during the early Weimar Republic.
  • D. 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.
  • E. Stephen Gaghan
    Stephen Gaghan is an American screenwriter and director best known for his politically charged, multi-narrative films such as "Traffic" and "Syriana."
  • 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_69ca82efbce081908179b4b9c65096eb completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb8bdc0388190bbbd4bdc5ac3adec completed April 2, 2026, 12:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69d257fe0e348190b55fbd38e21cff7c completed April 5, 2026, 12:39 p.m.
Created at: March 30, 2026, 8:49 p.m.