Triple

T18602266
Position Surface form Disambiguated ID Type / Status
Subject Brainerd Lakes Regional Airport E454645 entity
Predicate operator P179 FINISHED
Object City of Brainerd 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: City of Brainerd | Statement: [Brainerd Lakes Regional Airport, operator, City of Brainerd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Brainerd
Context triple: [Brainerd Lakes Regional Airport, operator, City of Brainerd]
  • A. Brainerd chosen
    Brainerd is a small city in central Minnesota, United States, known as a regional hub for outdoor recreation in the lakes area.
  • B. Chisago City, Minnesota
    Chisago City, Minnesota is a small lakeside community in eastern Minnesota known for its scenic natural surroundings and proximity to the Twin Cities metropolitan area.
  • C. Kasson, Minnesota
    Kasson, Minnesota is a small city in southeastern Minnesota known as a residential and commercial hub within Dodge County.
  • D. Fridley
    Fridley is a suburban city in Anoka County, Minnesota, located just north of Minneapolis along the Mississippi River.
  • E. Brownsville, Minnesota
    Brownsville, Minnesota is a small city along the Mississippi River in southeastern Minnesota known for its scenic river views and outdoor recreation.
  • 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_69d8d38bbe7c8190bdec3138e7d413c9 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e54751d7ec81909efc4867f649002e completed April 19, 2026, 9:21 p.m.
Created at: April 10, 2026, 11:45 a.m.