Triple

T12683430
Position Surface form Disambiguated ID Type / Status
Subject War Machine E303003 entity
Predicate producer P490 FINISHED
Object Jeremy Kleiner E95226 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: Jeremy Kleiner | Statement: [War Machine, producer, Jeremy Kleiner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeremy Kleiner
Context triple: [War Machine, producer, Jeremy Kleiner]
  • A. Jeremy Kleiner chosen
    Jeremy Kleiner is an American film producer known for his work on acclaimed films such as the civil rights drama "Selma."
  • B. David Klein
    David Klein is an American cinematographer best known for his frequent collaborations with filmmaker Kevin Smith and his work on independent films and television series.
  • C. Andrew Weisblum
    Andrew Weisblum is an American film editor known for his work on major feature films, including collaborations with directors like Darren Aronofsky and Wes Anderson.
  • D. Rich Kleiman
    Rich Kleiman is an American sports agent and entrepreneur best known as Kevin Durant’s longtime business partner and co-founder of the sports and entertainment company Boardroom and the investment firm Thirty Five Ventures.
  • E. Neil Kagan
    Neil Kagan is an American editor and author known for producing richly illustrated historical and reference books, particularly for National Geographic.
  • 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_69d7bdee64a08190801c6d470aefd723 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961d68358819095bdaab8adf1dcf0 completed April 10, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b8a79488190aaf95d4f2e20a7bc completed May 3, 2026, 12:49 a.m.
Created at: April 9, 2026, 5:21 p.m.