Triple

T14313632
Position Surface form Disambiguated ID Type / Status
Subject Shakopee, Minnesota E354896 entity
Predicate borderedBy P224 FINISHED
Object Savage, Minnesota E484178 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: Savage, Minnesota | Statement: [Shakopee, Minnesota, borderedBy, Savage, Minnesota]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Savage, Minnesota
Context triple: [Shakopee, Minnesota, borderedBy, Savage, Minnesota]
  • A. Savage, Minnesota chosen
    Savage, Minnesota is a suburban city in the Minneapolis–Saint Paul metropolitan area known for its residential communities and proximity to major regional highways and natural amenities.
  • B. Keewatin, Minnesota
    Keewatin, Minnesota is a small city on the Iron Range in northern Minnesota known historically for its taconite mining industry.
  • C. Mora, Minnesota
    Mora, Minnesota is a small city in east-central Minnesota that serves as the county seat of Kanabec County and a regional hub for the surrounding rural area.
  • D. Eitzen, Minnesota
    Eitzen, Minnesota is a small city located in southeastern Minnesota near the Iowa border.
  • E. Le Sueur, Minnesota
    Le Sueur, Minnesota is a small city in south-central Minnesota known historically for its food processing industry and location along the Minnesota River.
  • 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_69d8278ed42c8190b9f882dcce611347 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de85b49e5481909b9ffab2d922e284 completed April 14, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4687c6bc819088452892128c420e completed May 8, 2026, 2:12 a.m.
Created at: April 10, 2026, 1:12 a.m.