Triple

T18040168
Position Surface form Disambiguated ID Type / Status
Subject Thomas County E431628 entity
Predicate hasCity P316 FINISHED
Object Boston, 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: Boston, Georgia | Statement: [Thomas County, hasCity, Boston, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boston, Georgia
Context triple: [Thomas County, hasCity, Boston, Georgia]
  • A. Boston, Georgia chosen
    Boston, Georgia is a small rural city in southern Georgia known for its historic downtown and agricultural surroundings.
  • B. Washington, Georgia
    Washington, Georgia is a historic small city in Wilkes County known for its well-preserved antebellum architecture and role in early American and Civil War history.
  • C. Geneva, Georgia
    Geneva, Georgia is a small rural town located in west-central Georgia in the United States.
  • D. Newton, Georgia
    Newton, Georgia is a small city in southwestern Georgia that serves as the administrative and governmental center of Baker County.
  • E. Bremen, Georgia
    Bremen, Georgia is a small city in Haralson and Carroll counties in western Georgia, known as a regional hub along major transportation routes west of Atlanta.
  • 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_69d8b9050fb48190890155145deb0a66 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4bfece6448190b4ba96075715bcef completed April 19, 2026, 11:43 a.m.
Created at: April 10, 2026, 10:25 a.m.