Triple

T11918773
Position Surface form Disambiguated ID Type / Status
Subject Deborah Kerr E283597 entity
Predicate spouse P13 FINISHED
Object Peter Viertel E340165 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: Peter Viertel | Statement: [Deborah Kerr, spouse, Peter Viertel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Viertel
Context triple: [Deborah Kerr, spouse, Peter Viertel]
  • A. Peter Viertel chosen
    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.
  • B. Peter Riegert
    Peter Riegert is an American actor and director known for his roles in films such as "Animal House," "Local Hero," and "The Mask," as well as numerous television appearances.
  • C. Stephen Volk
    Stephen Volk is a British screenwriter and author best known for his work in supernatural and horror drama for film and television.
  • D. 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."
  • E. Philip Steuer
    Philip Steuer is a film producer best known for his work on major studio projects, including the Disney drama "Saving Mr. Banks."
  • 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_69d6ab2c07e88190ba13b0d21fd6cf33 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e8dff77481908cacf6ad03df34ac completed April 10, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69f440247cf4819084567f6e1005ef04 completed May 1, 2026, 5:54 a.m.
Created at: April 8, 2026, 9:44 p.m.