Triple

T16156368
Position Surface form Disambiguated ID Type / Status
Subject Jay Karnes E392053 entity
Predicate name P16 FINISHED
Object Jay Karnes E392053 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: Jay Karnes | Statement: [Jay Karnes, name, Jay Karnes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jay Karnes
Context triple: [Jay Karnes, name, Jay Karnes]
  • A. Jay Karnes chosen
    Jay Karnes is an American actor best known for his role as Detective Holland "Dutch" Wagenbach on the television crime drama series "The Shield."
  • B. Todd Karns
    Todd Karns was an American film and television actor best known for his role as Harry Bailey in the classic movie "It's a Wonderful Life."
  • C. Jon Kern
    Jon Kern is a software engineer and consultant best known as one of the original co-authors of the Agile Manifesto, helping to shape modern agile software development practices.
  • D. Ken Kelsch
    Ken Kelsch was an American cinematographer and occasional producer known for his gritty visual style and frequent collaborations with director Abel Ferrara.
  • E. Kevin Biegel
    Kevin Biegel is an American television writer and producer best known for co-creating the sitcom Cougar Town and working on shows like Scrubs and Enlisted.
  • 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_69d87f1c65e48190aa2b4c472e9bafc4 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21e5aa57c8190a9d89dd57e30318f completed April 17, 2026, 11:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00a5047a7c8190bac0ac9888547d16 completed May 10, 2026, 3:32 p.m.
Created at: April 10, 2026, 5:01 a.m.