Triple

T3197131
Position Surface form Disambiguated ID Type / Status
Subject Saboteur E66960 entity
Predicate screenwriter P2831 FINISHED
Object Peter Viertel
Peter Viertel was a German-born American novelist and screenwriter known for works like "White Hunter Black Heart" and for his contributions to mid-20th-century Hollywood cinema.
E340165 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: Peter Viertel | Statement: [Saboteur, screenwriter, Peter Viertel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Viertel
Context triple: [Saboteur, screenwriter, Peter Viertel]
  • A. Michael Wandmacher
    Michael Wandmacher is an American film and television composer known for his work on horror and action projects, including the score for "My Bloody Valentine 3D."
  • B. Philip Steuer
    Philip Steuer is a film producer best known for his work on major studio projects, including the Disney drama "Saving Mr. Banks."
  • C. Stephen Endlicher
    Stephen Endlicher was a 19th-century Austrian botanist and linguist known for his influential work in plant taxonomy and classification.
  • D. Michael Klein
    Michael Klein is the father of Canadian author and activist Naomi Klein.
  • E. Michael Filerman
    Michael Filerman was an American television producer best known for developing and producing popular prime-time soap operas during the 1970s and 1980s.
  • 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: Peter Viertel
Triple: [Saboteur, screenwriter, Peter Viertel]
Generated description
Peter Viertel was a German-born American novelist and screenwriter known for works like "White Hunter Black Heart" and for his contributions to mid-20th-century Hollywood cinema.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Peter Viertel
Target entity description: Peter Viertel was a German-born American novelist and screenwriter known for works like "White Hunter Black Heart" and for his contributions to mid-20th-century Hollywood cinema.
  • A. Michael Wandmacher
    Michael Wandmacher is an American film and television composer known for his work on horror and action projects, including the score for "My Bloody Valentine 3D."
  • B. Philip Steuer
    Philip Steuer is a film producer best known for his work on major studio projects, including the Disney drama "Saving Mr. Banks."
  • C. Stephen Endlicher
    Stephen Endlicher was a 19th-century Austrian botanist and linguist known for his influential work in plant taxonomy and classification.
  • D. Michael Klein
    Michael Klein is the father of Canadian author and activist Naomi Klein.
  • E. Michael Filerman
    Michael Filerman was an American television producer best known for developing and producing popular prime-time soap operas during the 1970s and 1980s.
  • 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_69ad8588ba18819086a10951c32ecb80 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada7192994819084817307065a25e2 completed March 8, 2026, 4:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2770201888190af6cbeded6d1ae56 completed March 12, 2026, 8:19 a.m.
NEDg Description generation batch_69b27b0289a08190ab3b9bd1d43b91ea completed March 12, 2026, 8:36 a.m.
NED2 Entity disambiguation (via description) batch_69b27badbe7881909e6215965e7c6907 completed March 12, 2026, 8:39 a.m.
Created at: March 8, 2026, 3:07 p.m.