Triple

T2142402
Position Surface form Disambiguated ID Type / Status
Subject Yatesville, Georgia E46787 entity
Predicate countrySubdivision P766 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: [Yatesville, Georgia, countrySubdivision, Upson County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Upson County
Context triple: [Yatesville, Georgia, countrySubdivision, 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. Crawford County
    Crawford County is a rural county in central Georgia known for its agricultural landscape and small-town communities west of Macon.
  • C. Van Buren County
    Van Buren County is a county in southwestern Michigan known for its Lake Michigan shoreline, agricultural areas, and small towns.
  • D. Winneshiek County
    Winneshiek County is a county in northeastern Iowa known for its scenic Driftless Area landscape, Norwegian-American heritage, and county seat of Decorah.
  • E. Warren County
    Warren County is a county in northeastern New York State known for encompassing much of the Adirondack Mountains and popular tourist destinations such as Lake George.
  • 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_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbe0543108190862dd9a4a861c758 completed March 7, 2026, 5:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae58d5535c8190b59293afe3a10834 completed March 9, 2026, 5:21 a.m.
Created at: March 4, 2026, 7:44 p.m.