Triple

T6392241
Position Surface form Disambiguated ID Type / Status
Subject Joel McKinnon Miller E143855 entity
Predicate name P16 FINISHED
Object Joel McKinnon Miller E143855 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: Joel McKinnon Miller | Statement: [Joel McKinnon Miller, name, Joel McKinnon Miller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joel McKinnon Miller
Context triple: [Joel McKinnon Miller, name, Joel McKinnon Miller]
  • A. Joel McKinnon Miller chosen
    Joel McKinnon Miller is an American character actor best known for playing the affable Detective Norm Scully on the television comedy series "Brooklyn Nine-Nine."
  • B. Michael Kube-McDowell
    Michael Kube-McDowell is an American science fiction author known for his novels, short stories, and contributions to major franchises such as Star Wars.
  • C. Jonah Platt
    Jonah Platt is an American actor and singer known for his work in musical theatre, television, and as part of the entertainment-industry Platt family.
  • D. Marc Tarpenning
    Marc Tarpenning is an American engineer and entrepreneur best known as a co-founder of electric vehicle and clean energy company Tesla, Inc.
  • E. Toby Huss
    Toby Huss is an American actor and voice actor known for his character roles in film and television, including work on series like "King of the Hill" and "Halt and Catch Fire."
  • 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_69c008db906c819096f3597d55d95432 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0687db4b881909dd84d5a947cc3e3 completed March 22, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640ba9e04819098713f5bea7ebdbc completed March 27, 2026, 8:32 a.m.
Created at: March 22, 2026, 4:34 p.m.