Triple

T15483287
Position Surface form Disambiguated ID Type / Status
Subject South Georgia E376975 entity
Predicate hasCity P316 FINISHED
Object Douglas, Georgia E1101736 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: Douglas, Georgia | Statement: [South Georgia, hasCity, Douglas, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Douglas, Georgia
Context triple: [South Georgia, hasCity, Douglas, Georgia]
  • A. Douglas, Georgia chosen
    Douglas, Georgia is a small city in south-central Georgia that serves as the county seat of Coffee County and a regional hub for agriculture and industry.
  • B. Douglasville, Georgia
    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.
  • C. Du Pont, Georgia
    Du Pont, Georgia is a small rural town in southern Georgia, United States, known for its historic ties to the region’s timber and railroad industries.
  • D. Guyton, Georgia
    Guyton, Georgia is a small city in southeastern Georgia known for its historic charm and role as a residential community within the Savannah metropolitan area.
  • E. Blakely, Georgia
    Blakely, Georgia is a small city in southwestern Georgia that serves as the administrative and economic center of Early County.
  • 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f8e6ff08190b130b3a38f4190e7 completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff365b3980819094d3ca0b7766009c completed May 9, 2026, 1:27 p.m.
Created at: April 10, 2026, 3:42 a.m.