Triple

T5317332
Position Surface form Disambiguated ID Type / Status
Subject Emma (1996 film) E121582 entity
Predicate producer P490 FINISHED
Object Steven Haft E403079 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: Steven Haft | Statement: [Emma (1996 film), producer, Steven Haft]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Steven Haft
Context triple: [Emma (1996 film), producer, Steven Haft]
  • A. Steven Haft chosen
    Steven Haft is an American film producer known for his work on movies such as the cult Halloween comedy "Hocus Pocus."
  • B. Josh Kesselman
    Josh Kesselman is a film and television producer best known for his work as an executive producer on projects such as the series "The Great."
  • C. Jake Adelstein
    Jake Adelstein is an American journalist and author best known for his memoir "Tokyo Vice," which chronicles his experiences reporting on crime and the yakuza for a major Japanese newspaper.
  • D. Steven Baigelman
    Steven Baigelman is an American screenwriter and producer known for his work on biographical and crime dramas in film and television.
  • E. Johnny Gandelsman
    Johnny Gandelsman is a Grammy-winning violinist and producer known for his work with ensembles like Brooklyn Rider and the Silk Road Ensemble, as well as for his innovative solo projects.
  • 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_69bd463d956c819088105c3db802c017 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd854fd07c8190b4f1c3c8e618c308 completed March 20, 2026, 5:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfe61a2cd8819089ea67309d284be4 completed March 22, 2026, 12:52 p.m.
Created at: March 20, 2026, 1:59 p.m.