Triple

T20276305
Position Surface form Disambiguated ID Type / Status
Subject GA-02 E503025 entity
Predicate hasCity P316 FINISHED
Object Camilla, 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: Camilla, Georgia | Statement: [GA-02, hasCity, Camilla, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Camilla, Georgia
Context triple: [GA-02, hasCity, Camilla, Georgia]
  • A. Camilla, Georgia chosen
    Camilla, Georgia is a small city in Mitchell County known as an agricultural and commercial center in the southwestern part of the state.
  • B. Cumming, Georgia
    Cumming, Georgia is a small city in Forsyth County that serves as a suburban hub within the Atlanta metropolitan area.
  • C. Philema, Georgia
    Philema, Georgia is a small unincorporated community located in rural Lee County in the southwestern part of the state.
  • D. Hartwell, Georgia
    Hartwell, Georgia is a small city in northeastern Georgia that serves as a gateway to outdoor recreation and tourism on Lake Hartwell.
  • E. St. Marys, Georgia
    St. Marys, Georgia is a historic coastal town in southeastern Georgia known as a gateway to Cumberland Island and the surrounding marshes and waterways.
  • 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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e675e3df68819096fb859bc92a0da1 completed April 20, 2026, 6:52 p.m.
Created at: April 16, 2026, 10:32 a.m.