Triple

T9345035
Position Surface form Disambiguated ID Type / Status
Subject Douglas County, Georgia E224866 entity
Predicate hasCity P316 FINISHED
Object Douglasville, Georgia E411999 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: Douglasville, Georgia | Statement: [Douglas County, Georgia, hasCity, Douglasville, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Douglasville, Georgia
Context triple: [Douglas County, Georgia, hasCity, Douglasville, Georgia]
  • A. Douglasville, Georgia chosen
    Douglasville, Georgia is a suburban city in the Atlanta metropolitan area known for its historic downtown and role as a regional commercial and residential hub.
  • B. Snellville, Georgia
    Snellville, Georgia is a suburban city in Gwinnett County known for its residential communities, local parks, and proximity to Atlanta.
  • C. Dunwoody, Georgia
    Dunwoody, Georgia is a suburban city in the Atlanta metropolitan area known for its residential neighborhoods, shopping centers, and business districts.
  • D. Dacula, Georgia
    Dacula, Georgia is a small suburban city in Gwinnett County within the Atlanta metropolitan area.
  • E. Doraville, Georgia
    Doraville, Georgia is a small suburban city in the Atlanta metropolitan area known for its diverse population and mix of residential, industrial, and commercial districts.
  • 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_69ca842993248190a79ab06968994b86 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4f0ce7b881908714ab526d94fa1d completed April 1, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69d139bfc054819084b39c16b7bdb2be completed April 4, 2026, 4:18 p.m.
Created at: March 30, 2026, 7:41 p.m.