Triple

T15845053
Position Surface form Disambiguated ID Type / Status
Subject North Georgia E384192 entity
Predicate contains P35 FINISHED
Object Calhoun, Georgia E353011 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: Calhoun, Georgia | Statement: [North Georgia, contains, Calhoun, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Calhoun, Georgia
Context triple: [North Georgia, contains, Calhoun, Georgia]
  • A. Calhoun, Georgia chosen
    Calhoun, Georgia is a small city in northwest Georgia known as the county seat of Gordon County and a regional hub along Interstate 75.
  • B. Colquitt, Georgia
    Colquitt, Georgia is a small city in southwest Georgia known as the cultural and economic hub of Miller County.
  • C. Baxley, Georgia
    Baxley, Georgia is a small city in Appling County known for its rural character and proximity to major energy infrastructure in southeastern Georgia.
  • 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. 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_69d86da422088190aac39e32e6c68429 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e142eb20088190bb45e37ce3291ef2 completed April 16, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a001f7f439c8190b4bcd84e35aa291e completed May 10, 2026, 6:02 a.m.
Created at: April 10, 2026, 4:50 a.m.