Triple

T23039051
Position Surface form Disambiguated ID Type / Status
Subject DeKalb County School District E573685 entity
Predicate servesCommunity P82 FINISHED
Object Clarkston, Georgia NE NERFINISHED

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: Clarkston, Georgia | Statement: [DeKalb County School District, servesCommunity, Clarkston, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Clarkston, Georgia
Context triple: [DeKalb County School District, servesCommunity, Clarkston, Georgia]
  • A. Clarkston, Georgia chosen
    Clarkston, Georgia is a small, diverse city in the Atlanta metropolitan area known for its large refugee and immigrant population.
  • B. Colquitt, Georgia
    Colquitt, Georgia is a small city in southwest Georgia known as the cultural and economic hub of Miller County.
  • C. 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.
  • D. Blakely, Georgia
    Blakely, Georgia is a small city in southwestern Georgia that serves as the administrative and economic center of Early County.
  • E. St. Marys, Georgia
    St. Marys, Georgia is a historic coastal town in southeastern Georgia known as a gateway to Cumberland Island and the surrounding marshes and waterways.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245b911188190bc3d96326c847969 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f185121da0819095b523d7d2c923ab completed April 29, 2026, 4:12 a.m.
Created at: April 17, 2026, 3:53 p.m.