Triple

T1108083
Position Surface form Disambiguated ID Type / Status
Subject The Girl on the Train (2016 film) E25531 entity
Predicate producer P490 FINISHED
Object Marc Platt E130854 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: Marc Platt | Statement: [The Girl on the Train (2016 film), producer, Marc Platt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marc Platt
Context triple: [The Girl on the Train (2016 film), producer, Marc Platt]
  • A. Marc Platt chosen
    Marc Platt is an American film and theater producer known for major projects such as "La La Land," "Wicked," and "Bridge of Spies."
  • B. Josh Harris
    Josh Harris is an American billionaire investor and sports team owner best known as a co-founder of Apollo Global Management and the principal owner of multiple professional franchises, including the NFL’s Washington Commanders.
  • C. John Pleffer
    John Pleffer is an Australian architect best known as the husband of acclaimed film director Gillian Armstrong.
  • D. Eric Fellner
    Eric Fellner is a British film producer and co-chairman of Working Title Films, known for overseeing numerous successful UK and international movies.
  • E. Marc Randolph
    Marc Randolph is an American entrepreneur and co-founder of Netflix who played a key role in pioneering the subscription-based streaming and DVD-by-mail business model.
  • 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_69a49428d4448190b3b36991ceae87ce completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b9e47e4881908928900df72781f0 completed March 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8f6969a8819091383fb1172ceeee completed March 7, 2026, 8:49 p.m.
Created at: March 1, 2026, 7:43 p.m.