Triple

T4730045
Position Surface form Disambiguated ID Type / Status
Subject Sumter County, Georgia E104982 entity
Predicate hasTown P847 FINISHED
Object De Soto, Georgia E174803 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: De Soto, Georgia | Statement: [Sumter County, Georgia, hasTown, De Soto, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: De Soto, Georgia
Context triple: [Sumter County, Georgia, hasTown, De Soto, Georgia]
  • A. De Soto, Georgia chosen
    De Soto, Georgia is a small rural city located in southwestern Georgia in the United States.
  • B. Calhoun, Georgia
    Calhoun, Georgia is a small city in northwest Georgia known as the county seat of Gordon County and a regional hub along Interstate 75.
  • C. Fortson, Georgia
    Fortson, Georgia is an unincorporated community in Muscogee County known primarily as a residential suburb of Columbus.
  • D. Townsend, Georgia
    Townsend, Georgia is a small unincorporated community in coastal southeastern Georgia known for its rural character and proximity to marshlands and waterways.
  • E. Vidette, Georgia
    Vidette, Georgia is a small unincorporated rural community located in Burke County in the eastern part of the state.
  • 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_69bd43ee52048190b81a4f066534ffb3 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd646135c881909030c21a163cc619 completed March 20, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5c8a20a88190a668251abbc1c7c8 completed March 21, 2026, 8:53 a.m.
Created at: March 20, 2026, 1:19 p.m.