Triple

T6621261
Position Surface form Disambiguated ID Type / Status
Subject Lapeer County E149677 entity
Predicate borderedBy P224 FINISHED
Object Tuscola County E346143 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: Tuscola County | Statement: [Lapeer County, borderedBy, Tuscola County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tuscola County
Context triple: [Lapeer County, borderedBy, Tuscola County]
  • A. Tuscola County, Michigan chosen
    Tuscola County, Michigan is a largely rural county in Michigan's Thumb region, known for its agricultural landscape and small communities.
  • B. Waushara County
    Waushara County is a rural county in central Wisconsin known for its lakes, forests, and outdoor recreation.
  • C. Shiawassee County
    Shiawassee County is a largely rural county in central Michigan known for its small towns, agricultural landscape, and location between the Lansing and Flint metropolitan areas.
  • D. Allegan County
    Allegan County is a county in southwestern Michigan known for its mix of Lake Michigan shoreline, agricultural land, and small towns.
  • E. Bayfield County
    Bayfield County is a county in northern Wisconsin known for its Lake Superior shoreline, Apostle Islands, and extensive outdoor recreation opportunities.
  • 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_69c687ed8a9c81908bb671717cb192ef completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af7ccaa481908b383b4fd671fa78 completed March 27, 2026, 4:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f78f667c81908c2de74009c8e073 completed March 27, 2026, 9:33 p.m.
Created at: March 27, 2026, 1:58 p.m.