Triple

T9735635
Position Surface form Disambiguated ID Type / Status
Subject Murderball E236049 entity
Predicate producer P490 FINISHED
Object Jeffrey Mandel E524978 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: Jeffrey Mandel | Statement: [Murderball, producer, Jeffrey Mandel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeffrey Mandel
Context triple: [Murderball, producer, Jeffrey Mandel]
  • A. Daniel Mandell
    Daniel Mandell was an American film editor renowned for his work on numerous classic Hollywood films and for winning multiple Academy Awards for Best Film Editing.
  • B. 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.
  • C. Mitch Kertzman
    Mitch Kertzman is an American technology executive and entrepreneur best known for his leadership roles in the software and semiconductor industries, including at companies like LSI Logic and Sybase.
  • D. Doug Mankoff chosen
    Doug Mankoff is a film and television producer known for financing and executive producing a wide range of independent and prestige projects.
  • E. Eric Dinowitz
    Eric Dinowitz is a New York City Council member representing parts of the Bronx, including neighborhoods such as Spuyten Duyvil.
  • 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_69ca84d313e88190983ee6ffd0ef60d2 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9eee70d48190af5a833d7b33aaa5 completed April 1, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69d20d048c5081908c891633129dc5d6 completed April 5, 2026, 7:19 a.m.
Created at: March 30, 2026, 8:22 p.m.