Triple

T18416838
Position Surface form Disambiguated ID Type / Status
Subject Gaear Grimsrud E441914 entity
Predicate associatedWithCharacter P1481 FINISHED
Object Jerry Lundegaard 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: Jerry Lundegaard | Statement: [Gaear Grimsrud, associatedWithCharacter, Jerry Lundegaard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jerry Lundegaard
Context triple: [Gaear Grimsrud, associatedWithCharacter, Jerry Lundegaard]
  • A. Jerry Lundegaard chosen
    Jerry Lundegaard is the financially desperate, bumbling car salesman whose botched crime scheme drives the darkly comic plot of the film "Fargo."
  • B. Miles Straume
    Miles Straume is a sarcastic, ghost-communicating medium and member of the freighter team on the television series "Lost."
  • C. Jacob Stroud
    Jacob Stroud was an early American settler and landowner who founded the community that became Stroudsburg, Pennsylvania.
  • D. Jack Deerson
    Jack Deerson is a cinematographer best known for his work on the 1971 road movie "Two-Lane Blacktop."
  • E. Jack McFarland
    Jack McFarland is a flamboyant, aspiring actor and Will Truman’s exuberant best friend on the sitcom "Will & Grace," known for his over-the-top personality and comedic antics.
  • 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_69d8b9eb8a508190a942fd75ebd8b1dc completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e51a284b608190b77c360a72aceb7a completed April 19, 2026, 6:08 p.m.
Created at: April 10, 2026, 10:47 a.m.