Triple

T14498559
Position Surface form Disambiguated ID Type / Status
Subject Chestatee River E359568 entity
Predicate flowsThrough P225 FINISHED
Object Dahlonega, Georgia E42810 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: Dahlonega, Georgia | Statement: [Chestatee River, flowsThrough, Dahlonega, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dahlonega, Georgia
Context triple: [Chestatee River, flowsThrough, Dahlonega, Georgia]
  • A. Dahlonega, Georgia chosen
    Dahlonega, Georgia is a historic North Georgia mountain town best known as the site of one of the first major U.S. gold rushes and now a popular tourist destination with a preserved 19th-century downtown.
  • B. Blakely, Georgia
    Blakely, Georgia is a small city in southwestern Georgia that serves as the administrative and economic center of Early County.
  • C. 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.
  • D. Tallapoosa, Georgia
    Tallapoosa, Georgia is a small city in Haralson County in western Georgia, known for its historic downtown and location near the Alabama state line.
  • E. De Soto, Georgia
    De Soto, Georgia is a small rural city located in southwestern Georgia in the United States.
  • 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_69d8279740308190af9df93a3af8592e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de9311cc748190880c784f173b7f2b completed April 14, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a420040819097ee73390d625338 completed May 8, 2026, 5:53 a.m.
Created at: April 10, 2026, 1:21 a.m.