Triple

T20481237
Position Surface form Disambiguated ID Type / Status
Subject Moultrie, Georgia E502456 entity
Predicate near P350 FINISHED
Object Valdosta, 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: Valdosta, Georgia | Statement: [Moultrie, Georgia, near, Valdosta, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valdosta, Georgia
Context triple: [Moultrie, Georgia, near, Valdosta, Georgia]
  • A. Valdosta, Georgia chosen
    Valdosta, Georgia is a small city in southern Georgia known as a regional hub for education, retail, and sports, particularly high school football.
  • B. Odum, Georgia
    Odum, Georgia is a small town in southeastern Georgia, United States, located in Wayne County.
  • C. Alvaton, Georgia
    Alvaton, Georgia is an unincorporated rural community located in Meriwether County in the west-central part of the state.
  • D. Jakin, Georgia
    Jakin, Georgia is a small rural city in southwestern Georgia known for its agricultural surroundings and close-knit community.
  • E. Vidalia, Georgia
    Vidalia, Georgia is a small city in southeastern Georgia best known as the namesake and primary production area of the famous sweet Vidalia onions.
  • 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_69e0b4af32848190aea80682b44d5d6e completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69b56dd248190b6bc4e513aff3c9c completed April 20, 2026, 9:32 p.m.
Created at: April 16, 2026, 11:34 a.m.