Triple

T4730043
Position Surface form Disambiguated ID Type / Status
Subject Sumter County, Georgia E104982 entity
Predicate hasTown P847 FINISHED
Object Plains, Georgia E84456 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: Plains, Georgia | Statement: [Sumter County, Georgia, hasTown, Plains, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Plains, Georgia
Context triple: [Sumter County, Georgia, hasTown, Plains, Georgia]
  • A. Plains, Georgia, United States chosen
    Plains, Georgia, United States, is a small rural town best known as the hometown of former U.S. President Jimmy Carter.
  • B. White Plains, Georgia
    White Plains, Georgia is a small historic town in Greene County known for its rural character and 19th-century roots in east-central Georgia.
  • C. De Soto, Georgia
    De Soto, Georgia is a small rural city located in southwestern Georgia in the United States.
  • D. Blakely, Georgia
    Blakely, Georgia is a small city in southwestern Georgia that serves as the administrative and economic center of Early County.
  • E. Valdosta, Georgia
    Valdosta, Georgia is a small city in southern Georgia known as a regional hub for education, retail, and sports, particularly high school football.
  • 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_69be10a4bc0481908935278afb13503d completed March 21, 2026, 3:29 a.m.
Created at: March 20, 2026, 1:19 p.m.