Triple

T9612128
Position Surface form Disambiguated ID Type / Status
Subject Cleveland metropolitan area E232126 entity
Predicate includesCounty P5971 FINISHED
Object Medina County E577555 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: Medina County | Statement: [Cleveland metropolitan area, includesCounty, Medina County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Medina County
Context triple: [Cleveland metropolitan area, includesCounty, Medina County]
  • A. Medina County chosen
    Medina County is a suburban-rural county in northern Ohio known for its historic town squares, growing residential communities, and proximity to the Cleveland metropolitan area.
  • B. Medina County, Texas
    Medina County, Texas is a largely rural county in south-central Texas known for its agricultural economy, small towns, and proximity to the San Antonio metropolitan area.
  • C. Wood County
    Wood County is a county in central Wisconsin known for its mix of small cities, agricultural areas, and paper industry heritage.
  • D. Brown County
    Brown County is a county in northeastern Wisconsin that includes the city of Green Bay and operates various public facilities and services for its residents.
  • E. Cypress County
    Cypress County is a rural municipal district in southeastern Alberta, Canada, surrounding the city of Medicine Hat and encompassing a mix of agricultural land, small communities, and natural areas.
  • 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_69ca8485a90c819094fe40b42fde9d70 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9a87764481909ab96cd2ab96d14b completed April 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69d179513f9081909bcd9a456c640ba3 completed April 4, 2026, 8:49 p.m.
Created at: March 30, 2026, 8:09 p.m.