Triple

T22095914
Position Surface form Disambiguated ID Type / Status
Subject Shadow of the Thin Man E546031 entity
Predicate editor P1954 FINISHED
Object Robert Kern NE NERFINISHED

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: Robert Kern | Statement: [Shadow of the Thin Man, editor, Robert Kern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Robert Kern
Context triple: [Shadow of the Thin Man, editor, Robert Kern]
  • A. Robert Kern chosen
    Robert Kern was an American film editor active during Hollywood’s classic studio era, known for his work on numerous prominent MGM productions.
  • B. Greg Ewing
    Greg Ewing is a computer scientist and software developer best known for creating Pyrex, an early language for writing Python C extensions more easily.
  • C. Raymond Hettinger
    Raymond Hettinger is a prominent Python core developer and software engineer known for his major contributions to the language’s standard library, especially in areas like iteration tools and data structures.
  • D. Nick Coghlan
    Nick Coghlan is a prominent Python core developer and software engineer known for his influential work on Python’s governance, documentation, and language design.
  • E. Ben Finney
    Ben Finney was an anthropologist and pioneer of experimental archaeology best known for reviving traditional Polynesian navigation and co-founding the Polynesian Voyaging Society.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e36d03c8190a83a1ba802b7231b completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f128e8f1f48190a5f1d9e96a6de688 completed April 28, 2026, 9:38 p.m.
Created at: April 16, 2026, 8:29 p.m.