Triple

T22803395
Position Surface form Disambiguated ID Type / Status
Subject Tramps E564463 entity
Predicate producer P490 FINISHED
Object David Kaplan 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: David Kaplan | Statement: [Tramps, producer, David Kaplan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Kaplan
Context triple: [Tramps, producer, David Kaplan]
  • A. David Kaplan
    David Kaplan is an American philosopher best known for his influential work in the philosophy of language and logic, particularly on demonstratives, indexicals, and the semantics of context.
  • B. David Kaplan chosen
    David Kaplan is a film producer known for his work on independent and genre films, including serving as a producer on the movie "Kicks."
  • C. Neil Kaplan
    Neil Kaplan is an American voice actor best known for portraying heroic characters in animation and video games, including Optimus Prime in the "Transformers: Robots in Disguise" series.
  • D. Jonathan Kaplan
    Jonathan Kaplan is an American film and television director best known for his work on the acclaimed 1988 courtroom drama "The Accused."
  • E. Greg Kaplan
    Greg Kaplan is an economist known for his research on household heterogeneity, consumption, and macroeconomic policy, and for his contributions to modern macroeconomic modeling.
  • 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_69e245823f4c8190ade442cdcc2c224a completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17d5a7c2881909a7aaacddd09f00c completed April 29, 2026, 3:39 a.m.
Created at: April 17, 2026, 3:31 p.m.