Triple

T4629048
Position Surface form Disambiguated ID Type / Status
Subject Mount Massive E101168 entity
Predicate county P75 FINISHED
Object Lake County E445187 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: [Mount Massive, county, Lake County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake County
Context triple: [Mount Massive, county, Lake County]
  • A. Lake County
    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. Lake County chosen
    Lake County is a high-altitude county in central Colorado known for encompassing the historic mining city of Leadville and surrounding Rocky Mountain terrain.
  • E. 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.
  • 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_69bd43d0497c8190ac23c65c5804846a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a300e6081909fa9f504aada33ea completed March 20, 2026, 2:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfab4f4808190920e420f566dec9b completed March 21, 2026, 1:56 a.m.
Created at: March 20, 2026, 1:13 p.m.