Triple

T5338871
Position Surface form Disambiguated ID Type / Status
Subject Anatomy of a Murder E123894 entity
Predicate editor P1954 FINISHED
Object Louis R. Loeffler E333708 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: Louis R. Loeffler | Statement: [Anatomy of a Murder, editor, Louis R. Loeffler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Louis R. Loeffler
Context triple: [Anatomy of a Murder, editor, Louis R. Loeffler]
  • A. Louis Loeffler chosen
    Louis Loeffler was an American film editor active during Hollywood’s studio era, known for his work on numerous major 20th Century Fox productions.
  • B. Thomas Tamm
    Thomas Tamm is a former U.S. Justice Department lawyer known for exposing the Bush administration’s secret warrantless wiretapping program, code-named Stellar Wind.
  • C. Albert F. Mummery
    Albert F. Mummery was a pioneering 19th-century British mountaineer renowned for his bold, innovative ascents in the Alps and Himalayas and for helping shape modern alpinism.
  • D. Alfred P. Boller
    Alfred P. Boller was an American civil engineer known for designing major infrastructure projects in the late 19th and early 20th centuries.
  • E. Werner R. Heymann
    Werner R. Heymann was a German composer best known for his sophisticated film scores in Hollywood’s Golden Age, particularly for classic comedies and romances.
  • 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_69bd464b07f8819095aa76577c9829e4 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd85c8415c819099a0b26e07360f01 completed March 20, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf33324ac08190a3785f1340097f68 completed March 22, 2026, 12:09 a.m.
Created at: March 20, 2026, 2 p.m.