Triple

T345546
Position Surface form Disambiguated ID Type / Status
Subject Georgia State Route 74 E6931 entity
Predicate passesThrough P225 FINISHED
Object Upson County E17106 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: Upson County | Statement: [Georgia State Route 74, passesThrough, Upson County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Upson County
Context triple: [Georgia State Route 74, passesThrough, Upson County]
  • A. Upson County chosen
    Upson County is a county in central Georgia, United States, known for its seat in Thomaston and its mix of rural communities and small-town industry.
  • B. Greene County
    Greene County is a rural county in southwestern Pennsylvania known for its Appalachian landscape, coal mining history, and small-town communities within the greater Pittsburgh region.
  • C. Pike County
    Pike County is a county in west-central Georgia, United States, known for its rural character and location within the Atlanta metropolitan area’s broader region.
  • D. Allegan County
    Allegan County is a county in southwestern Michigan known for its mix of Lake Michigan shoreline, agricultural land, and small towns.
  • E. Ottawa County
    Ottawa County is a county in western Michigan known for its Lake Michigan shoreline, agricultural communities, and cities such as Holland and Grand Haven.
  • 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_69a2e7951ba08190960e90823b5078f3 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2eb0240e88190bc70784772f5fa30 completed Feb. 28, 2026, 1:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a40ad03f5c819085d2c7686f4d2809 completed March 1, 2026, 9:45 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.