Triple

T20881957
Position Surface form Disambiguated ID Type / Status
Subject Telefon E514173 entity
Predicate producer P490 FINISHED
Object Irwin Winkler 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: Irwin Winkler | Statement: [Telefon, producer, Irwin Winkler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Irwin Winkler
Context triple: [Telefon, producer, Irwin Winkler]
  • A. Irwin Winkler chosen
    Irwin Winkler is an American film producer and director best known for producing the "Rocky" series and numerous other acclaimed Hollywood films.
  • B. David Katzenberg
    David Katzenberg is an American television and film producer and director known for co-creating the MTV series "The Hard Times of RJ Berger" and producing various comedy and horror projects.
  • C. Ilya Salkind
    Ilya Salkind is a film producer best known for co-producing the 1970s Superman films and other major international productions.
  • D. David Puttnam
    David Puttnam is a British film producer and politician best known for producing acclaimed films such as "Chariots of Fire" and "The Killing Fields."
  • E. Harold Mirisch
    Harold Mirisch was an American film producer and co-founder of the influential Mirisch Company, known for backing numerous acclaimed Hollywood movies in the mid-20th century.
  • 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_69e0b4f733f081908a401c0b7beb0b9f completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c67a33548190b0f5ba58b001d387 completed April 21, 2026, 12:36 a.m.
Created at: April 16, 2026, 12:46 p.m.