Triple

T3623149
Position Surface form Disambiguated ID Type / Status
Subject Diocese of Northern California E76773 entity
Predicate territoryIncludes P285 FINISHED
Object Lake County E146448 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: Lake County | Statement: [Diocese of Northern California, territoryIncludes, Lake County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake County
Context triple: [Diocese of Northern California, territoryIncludes, Lake County]
  • A. Lake County chosen
    Lake County is a rural county in Northern California known for Clear Lake, extensive vineyards and wineries, and its mountainous, volcanic landscape.
  • B. Lake County
    Lake County is a county in northwestern Indiana known for its industrial cities, including Gary, and its location along the southern shore of Lake Michigan.
  • C. Lake County
    Lake County is a county in northeastern Minnesota known for its North Shore scenery along Lake Superior and extensive forests and lakes.
  • D. Martin County
    Martin County is a coastal county on Florida’s Atlantic Treasure Coast known for its beaches, waterways, and mix of small cities and natural preserves.
  • E. Martin County
    Martin County is a sparsely populated rural county in western Texas known primarily for its agriculture and oil production.
  • 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_69ad85dae2fc81908d1ceadbc6af0089 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc2bc79008190abe6900adcbda8de completed March 8, 2026, 6:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5f59074e881908d346937da0b056e completed March 14, 2026, 11:56 p.m.
Created at: March 8, 2026, 3:23 p.m.