Triple

T17573602
Position Surface form Disambiguated ID Type / Status
Subject east-central Georgia E428000 entity
Predicate hasCity P316 FINISHED
Object Louisville, 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: Louisville, Georgia | Statement: [east-central Georgia, hasCity, Louisville, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Louisville, Georgia
Context triple: [east-central Georgia, hasCity, Louisville, Georgia]
  • A. Louisville, Georgia chosen
    Louisville, Georgia is a small historic city that briefly served as the capital of the U.S. state of Georgia in the late 18th century.
  • B. Lexington, Georgia
    Lexington, Georgia is a small historic city in Oglethorpe County that once served as the county seat and reflects early 19th-century Georgia history.
  • C. Springfield, Georgia
    Springfield, Georgia is a small city in Effingham County that serves as a residential and community hub within the greater Savannah metropolitan region.
  • D. Colquitt, Georgia
    Colquitt, Georgia is a small city in southwest Georgia known as the cultural and economic hub of Miller County.
  • E. Covington, Georgia
    Covington, Georgia is a small city in the eastern Atlanta metropolitan area known for its historic town square and frequent use as a filming location for movies and television shows.
  • 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_69d889e0385081908a04b66f4dd4bd0d completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e459330c788190907a02fc98e0e24b completed April 19, 2026, 4:25 a.m.
Created at: April 10, 2026, 5:50 a.m.