Triple

T17762682
Position Surface form Disambiguated ID Type / Status
Subject Arnold Classic E443418 entity
Predicate hasNotableWinner P2766 FINISHED
Object Jay Cutler 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: Jay Cutler | Statement: [Arnold Classic, hasNotableWinner, Jay Cutler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jay Cutler
Context triple: [Arnold Classic, hasNotableWinner, Jay Cutler]
  • A. Jay Cutler chosen
    Jay Cutler is an American professional bodybuilder best known for winning multiple Mr. Olympia titles in the 2000s and being one of the sport’s most prominent modern champions.
  • B. Jay Cutler
    Jay Cutler is a former American football quarterback best known for his NFL career with the Denver Broncos and Chicago Bears.
  • C. Camden Jack Cutler
    Camden Jack Cutler is the eldest son of television personality Kristin Cavallari and former NFL quarterback Jay Cutler.
  • D. Tony Romo
    Tony Romo is a former NFL quarterback best known for his prolific passing career with the Dallas Cowboys and later work as a prominent football broadcaster.
  • E. Andy Dalton
    Andy Dalton is an American NFL quarterback best known for his tenure as the longtime starter for the Cincinnati Bengals, where he led multiple playoff appearances.
  • 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_69d8b9edf16c8190a59ebd245d378f4f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e485f887ac81908c896a50175692b9 completed April 19, 2026, 7:36 a.m.
Created at: April 10, 2026, 10:11 a.m.