Triple

T16679487
Position Surface form Disambiguated ID Type / Status
Subject Cause and Effect E405301 entity
Predicate producer P490 FINISHED
Object David Kosten E1074261 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 Kosten | Statement: [Cause and Effect, producer, David Kosten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Kosten
Context triple: [Cause and Effect, producer, David Kosten]
  • A. David Kosten chosen
    David Kosten is a British record producer and mixer known for his work with artists across indie, alternative, and pop music, including collaborations with acts like Bat for Lashes and Everything Everything.
  • B. Paul Darrow
    Paul Darrow was the son of famed American lawyer Clarence Darrow and a businessman who managed many of his father's financial affairs.
  • C. David Jaffe
    David Jaffe is an American video game designer and director best known for creating the God of War and Twisted Metal franchises.
  • D. John Karlen
    John Karlen was an American character actor best known for his roles in the gothic soap opera "Dark Shadows" and the crime drama series "Cagney & Lacey."
  • E. Rob Lord
    Rob Lord is a British film and television composer known for his eclectic, melodic scores across independent features and mainstream productions.
  • 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37d6e74ec81909ea95c3e4b0113ab completed April 18, 2026, 12:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a3e2ddc8190a59108cdf001dac2 completed May 10, 2026, 1:38 p.m.
Created at: April 10, 2026, 5:19 a.m.