Triple

T9467333
Position Surface form Disambiguated ID Type / Status
Subject Jay Silverheels E228303 entity
Predicate name P16 FINISHED
Object Jay Silverheels E228303 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 Silverheels | Statement: [Jay Silverheels, name, Jay Silverheels]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jay Silverheels
Context triple: [Jay Silverheels, name, Jay Silverheels]
  • A. Jay Silverheels chosen
    Jay Silverheels was a Canadian Mohawk actor best known for his iconic role as Tonto in the classic television series "The Lone Ranger."
  • B. David Ossman
    David Ossman is an American writer, comedian, and voice actor best known as a member of the satirical comedy group The Firesign Theatre.
  • C. Spike Feresten
    Spike Feresten is an American television writer, producer, and talk show host best known for his work on Seinfeld and his own late-night series Talkshow with Spike Feresten.
  • D. Irwin Keyes
    Irwin Keyes was an American character actor best known for his imposing physique and roles in films and TV shows such as "The Jeffersons" and various horror and comedy movies.
  • E. Ernest Menville
    Ernest Menville is a beleaguered plastic surgeon and mortician caught between two vain, immortal rivals in the dark comedy film "Death Becomes Her."
  • 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_69ca846fee388190a6ec273fd644b88b completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7fdd7d048190930a15cb2a2d99ea completed April 1, 2026, 8:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69d122ba3d948190a3fa947cd3cad63b completed April 4, 2026, 2:39 p.m.
Created at: March 30, 2026, 7:53 p.m.