Triple

T20471776
Position Surface form Disambiguated ID Type / Status
Subject Peggy Blumquist E502209 entity
Predicate alliesWith P435 FINISHED
Object Ed Blumquist 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: Ed Blumquist | Statement: [Peggy Blumquist, alliesWith, Ed Blumquist]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ed Blumquist
Context triple: [Peggy Blumquist, alliesWith, Ed Blumquist]
  • A. Ed Blumquist chosen
    Ed Blumquist is a mild-mannered butcher and central character in the second season of the television series "Fargo," whose life spirals into chaos after a deadly accident involving his wife.
  • B. Brian Swardstrom
    Brian Swardstrom is a prominent American talent agent and partner at United Talent Agency, known for representing acclaimed actors and filmmakers.
  • C. Matt Keeslar
    Matt Keeslar is an American actor known for his work in film and television, including prominent roles in science fiction and fantasy adaptations.
  • D. Don Brautigam
    Don Brautigam was an American illustrator best known for his striking, realistic cover art for horror and thriller novels, including works by Stephen King.
  • E. Todd Boekelheide
    Todd Boekelheide is an American film composer and sound editor known for his work on numerous documentaries and feature films, including Academy Award–winning projects.
  • 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_69e0b4ae5f1081908768b0c9a3a0bf38 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6996197908190b6570e2a7fd6cf67 completed April 20, 2026, 9:23 p.m.
Created at: April 16, 2026, 11:33 a.m.