Triple

T20340521
Position Surface form Disambiguated ID Type / Status
Subject Debby Boone E495726 entity
Predicate relative P37 FINISHED
Object Red Foley 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: Red Foley | Statement: [Debby Boone, relative, Red Foley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Red Foley
Context triple: [Debby Boone, relative, Red Foley]
  • A. Red Foley chosen
    Red Foley was a pioneering American country music singer, guitarist, and radio/TV star whose smooth vocal style and gospel recordings helped shape the genre in the mid-20th century.
  • B. Lou Frizzell
    Lou Frizzell was an American character actor and voice actor known for his supporting roles in film and television during the mid-20th century.
  • C. Faron Young
    Faron Young was an American country music singer and songwriter, known for hits like "Hello Walls" and his influential role in the honky-tonk and Nashville sound eras.
  • D. Floyd Red Crow Westerman
    Floyd Red Crow Westerman was a Native American actor, musician, and activist known for his prominent roles in film and television and his advocacy for Indigenous rights.
  • E. John Frizzell
    John Frizzell is an American film and television composer known for scoring a wide range of genre films, including prominent horror and thriller titles.
  • 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_69e0b4a3320881909495ae8bc30bc2dc completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6783533a881909a12311bb9c66542 completed April 20, 2026, 7:02 p.m.
Created at: April 16, 2026, 11:23 a.m.