Triple

T12436921
Position Surface form Disambiguated ID Type / Status
Subject Lakemoor, Illinois E297167 entity
Predicate county P75 FINISHED
Object Lake County E640164 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: [Lakemoor, Illinois, county, Lake County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake County
Context triple: [Lakemoor, Illinois, county, Lake County]
  • A. 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.
  • B. Lake County
    Lake County is a rural county in western Montana known for encompassing much of Flathead Lake and parts of the Flathead Indian Reservation.
  • C. Lake County chosen
    Lake County is a county in northeastern Illinois, north of Chicago, known for its suburban communities, forest preserves, and location along Lake Michigan.
  • D. Lake County
    Lake County is a rural county in Northern California known for Clear Lake, extensive vineyards and wineries, and its mountainous, volcanic landscape.
  • E. Lake County
    Lake County is a county in northeastern Minnesota known for its North Shore scenery along Lake Superior and extensive forests and lakes.
  • 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d8c8fd481909b35ac504127a1b6 completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f06d16481909ed2eb5195ebd7e4 completed May 2, 2026, 6:14 p.m.
Created at: April 8, 2026, 9:55 p.m.