Triple

T15312000
Position Surface form Disambiguated ID Type / Status
Subject Gold (2016 film) E366059 entity
Predicate producer P490 FINISHED
Object John Zinman
John Zinman is an American screenwriter and producer known for his work on film and television projects such as the drama film "Gold" (2016).
 E1167265 NE FINISHED

How this triple was built (4 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: John Zinman | Statement: [Gold (2016 film), producer, John Zinman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John Zinman
Context triple: [Gold (2016 film), producer, John Zinman]
  • A. John Zinman
    John Zinman is a film and television screenwriter best known for co-writing the action-adventure movie "Lara Croft: Tomb Raider."
  • B. Edward Zorinsky
    Edward Zorinsky was a U.S. Senator from Nebraska and former mayor of Omaha known for his moderate Democratic politics and service in the late 20th century.
  • C. Don Zimmerman
    Don Zimmerman is a film editor known for his work on major Hollywood movies, including the family adventure-comedy "Night at the Museum."
  • D. Jonathan Zalben
    Jonathan Zalben is a film and television composer known for scoring a variety of independent features and documentaries.
  • E. Daniel Zelman
    Daniel Zelman is an American actor, screenwriter, and television producer known for co-creating the legal thriller series "Damages."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: John Zinman
Triple: [Gold (2016 film), producer, John Zinman]
Generated description
John Zinman is an American screenwriter and producer known for his work on film and television projects such as the drama film "Gold" (2016).
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: John Zinman
Target entity description: John Zinman is an American screenwriter and producer known for his work on film and television projects such as the drama film "Gold" (2016).
  • A. John Zinman
    John Zinman is a film and television screenwriter best known for co-writing the action-adventure movie "Lara Croft: Tomb Raider."
  • B. Edward Zorinsky
    Edward Zorinsky was a U.S. Senator from Nebraska and former mayor of Omaha known for his moderate Democratic politics and service in the late 20th century.
  • C. Don Zimmerman
    Don Zimmerman is a film editor known for his work on major Hollywood movies, including the family adventure-comedy "Night at the Museum."
  • D. Jonathan Zalben
    Jonathan Zalben is a film and television composer known for scoring a variety of independent features and documentaries.
  • E. Daniel Zelman
    Daniel Zelman is an American actor, screenwriter, and television producer known for co-creating the legal thriller series "Damages."
  • F. None of above. chosen

Provenance (5 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03cd2d5a88190aead748920f93d47 completed April 16, 2026, 1:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff56b4c6c881908ac7887a88f80829 completed May 9, 2026, 3:45 p.m.
NEDg Description generation batch_69ff5ac2aa188190804f801497ca16df completed May 9, 2026, 4:03 p.m.
NED2 Entity disambiguation (via description) batch_69ff5b211a7881908b82be108dd76122 completed May 9, 2026, 4:04 p.m.
Created at: April 10, 2026, 3:16 a.m.