Triple

T21737747
Position Surface form Disambiguated ID Type / Status
Subject Jesse Plemons E536570 entity
Predicate notableWork P4 FINISHED
Object Fargo 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: Fargo | Statement: [Jesse Plemons, notableWork, Fargo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fargo
Context triple: [Jesse Plemons, notableWork, Fargo]
  • A. Fargo chosen
    Fargo is a 1996 darkly comedic crime film by the Coen brothers, acclaimed for its distinctive blend of Midwestern noir, quirky characters, and sharp, offbeat dialogue.
  • B. Fargo
    Fargo is the NATO reporting name for the Mikoyan-Gurevich MiG-9, an early Soviet jet fighter developed shortly after World War II.
  • C. Fargo, North Dakota
    Fargo, North Dakota is the largest city in the state and a regional economic, cultural, and educational hub located along the Red River in the eastern part of North Dakota.
  • D. Moorhead
    Moorhead is a small town in Sunflower County, Mississippi, known historically as a railroad junction in the Mississippi Delta region.
  • E. Grand Forks, North Dakota
    Grand Forks, North Dakota is a city in the northeastern part of the state known for its Air Force base, regional university, and role as a strategic military and economic center in the Upper Midwest.
  • 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_69e0c46df5448190b4322127ffc4c690 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69effd0d33dc81908a4a79abc33355d1 completed April 28, 2026, 12:19 a.m.
Created at: April 16, 2026, 6:49 p.m.