Triple

T11292767
Position Surface form Disambiguated ID Type / Status
Subject Gracie Gold E267367 entity
Predicate formerCoach P4378 FINISHED
Object Frank Carroll E197732 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: Frank Carroll | Statement: [Gracie Gold, formerCoach, Frank Carroll]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frank Carroll
Context triple: [Gracie Gold, formerCoach, Frank Carroll]
  • A. Frank Carroll chosen
    Frank Carroll is a renowned American figure skating coach best known for guiding multiple world and Olympic medalists, including Michelle Kwan.
  • B. Frank Boucher
    Frank Boucher was a Canadian Hall of Fame ice hockey centre and coach best known for his stellar play with the New York Rangers in the NHL.
  • C. Cecil Layendecker
    Cecil Layendecker is a relatively obscure individual known primarily by name, with no widely documented public achievements or biographical details.
  • D. Ronald Colbert
    Ronald Colbert is an individual notable enough to be recognized as a bearer of the surname Colbert.
  • E. Frank Catton
    Frank Catton is a charismatic con artist and casino employee who is part of Danny Ocean’s heist crew in the Ocean’s film series.
  • 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_69d6aac993a08190a6f36445ebaf9a43 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e989fdac81909a4a75f1f68b55c6 completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f4a57d6881909a1e65744111ad8b completed April 19, 2026, 3:28 p.m.
Created at: April 8, 2026, 9:32 p.m.