Triple

T8182967
Position Surface form Disambiguated ID Type / Status
Subject Rincon, Georgia E191110 entity
Predicate nearbyCity P350 FINISHED
Object Guyton, Georgia E595862 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: Guyton, Georgia | Statement: [Rincon, Georgia, nearbyCity, Guyton, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guyton, Georgia
Context triple: [Rincon, Georgia, nearbyCity, Guyton, Georgia]
  • A. Guyton, Georgia chosen
    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.
  • B. Calhoun, Georgia
    Calhoun, Georgia is a small city in northwest Georgia known as the county seat of Gordon County and a regional hub along Interstate 75.
  • C. Argyle, Georgia
    Argyle, Georgia is a small rural town in southern Georgia known for its quiet community and location within Clinch County.
  • D. Blakely, Georgia
    Blakely, Georgia is a small city in southwestern Georgia that serves as the administrative and economic center of Early County.
  • 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_69ca82c4538081909404325aa5639483 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4c4db8748190aa785e0c70fac497 completed March 31, 2026, 4:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde72b95b08190834cb6f4da15ce95 completed April 2, 2026, 3:48 a.m.
Created at: March 30, 2026, 5:41 p.m.