Triple

T17176047
Position Surface form Disambiguated ID Type / Status
Subject Emmit Stussy E416861 entity
Predicate appearsIn P795 FINISHED
Object Fargo E95075 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: Fargo | Statement: [Emmit Stussy, appearsIn, Fargo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fargo
Context triple: [Emmit Stussy, appearsIn, 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 (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_69d886d5f34c8190b24564dfaa63f3fb completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3fc0cec448190b30466628a2ff23f completed April 18, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0148435f6081909bfc6cc1ef59d971 completed May 11, 2026, 3:08 a.m.
Created at: April 10, 2026, 5:37 a.m.