Triple

T1048139
Position Surface form Disambiguated ID Type / Status
Subject Roger Deakins E22629 entity
Predicate notableWork P4 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: [Roger Deakins, notableWork, Fargo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fargo
Context triple: [Roger Deakins, 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, 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.
  • C. 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.
  • D. Moorhead, Minnesota
    Moorhead, Minnesota is a city in northwestern Minnesota located along the Red River of the North, forming part of the Fargo–Moorhead metropolitan area.
  • E. Duluth
    Duluth is a major port city in northeastern Minnesota known for its shipping industry, scenic Lake Superior shoreline, and role as a regional transportation hub.
  • 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_69a493da02e081908c13ff5e02a0fe7a completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8b19a5c8190a532e025bd724088 completed March 1, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac6f0a15e48190a011c4aff5c285af completed March 7, 2026, 6:31 p.m.
Created at: March 1, 2026, 7:42 p.m.