Triple

T6598795
Position Surface form Disambiguated ID Type / Status
Subject After the Thin Man E148542 entity
Predicate editor P1954 FINISHED
Object Robert Kern E138041 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: Robert Kern | Statement: [After the Thin Man, editor, Robert Kern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Robert Kern
Context triple: [After 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. 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.
  • C. Chris Angelico
    Chris Angelico is a Python developer and community contributor known for his involvement in Python Enhancement Proposals, including co-authoring PEP 572.
  • D. David Flanagan
    David Flanagan is a software developer and technical author best known for his widely used programming books, including "JavaScript: The Definitive Guide."
  • E. Kent McCord
    Kent McCord is an American actor best known for his role as Officer Jim Reed on the television series "Adam-12."
  • 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_69c687e7b8688190811ffee72e096468 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aeeffdf0819090af7bba918bef84 completed March 27, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6e43224dc81909dea493a5ee2726e completed March 27, 2026, 8:10 p.m.
Created at: March 27, 2026, 1:56 p.m.