Triple

T1443851
Position Surface form Disambiguated ID Type / Status
Subject Marion County E31132 entity
Predicate borderedBy P224 FINISHED
Object Boone County E255304 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: Boone County | Statement: [Marion County, borderedBy, Boone County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boone County
Context triple: [Marion County, borderedBy, Boone County]
  • A. Boone County chosen
    Boone County is a county in central Indiana known for its mix of suburban communities like Zionsville and rural agricultural areas northwest of Indianapolis.
  • B. Boone County
    Boone County is a rural county in southern West Virginia known historically for its coal mining communities and Appalachian landscape.
  • C. Butler County
    Butler County is a rural county in south-central Alabama known for its pine forests, small towns, and location along the Interstate 65 corridor.
  • D. Butler County
    Butler County is a county in western Pennsylvania, north of Pittsburgh, known for its mix of suburban communities, rural landscapes, and growing industrial and service sectors.
  • E. Morgan County
    Morgan County is a county in northern Alabama known for its seat in Decatur and its role in the Huntsville-Decatur metropolitan area.
  • 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_69a4991633388190a4d61b5a98aa407a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c533a158819084d0917776edb6e5 completed March 1, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69af9893d2048190ac3b36c32f14b63d completed March 10, 2026, 4:05 a.m.
Created at: March 1, 2026, 8 p.m.