Triple

T20276311
Position Surface form Disambiguated ID Type / Status
Subject GA-02 E503025 entity
Predicate hasCity P316 FINISHED
Object Arlington, Georgia E176743 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: Arlington, Georgia | Statement: [GA-02, hasCity, Arlington, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arlington, Georgia
Context triple: [GA-02, hasCity, Arlington, Georgia]
  • A. Arlington, Georgia chosen
    Arlington, Georgia is a small rural city in the southwestern part of the state known historically for its agricultural economy and tight-knit community.
  • B. Colquitt, Georgia
    Colquitt, Georgia is a small city in southwest Georgia known as the cultural and economic hub of Miller County.
  • C. Hapeville, Georgia
    Hapeville, Georgia is a small city in the Atlanta metropolitan area known for its proximity to Hartsfield–Jackson Atlanta International Airport and its historic downtown.
  • D. Springfield, Georgia
    Springfield, Georgia is a small city in Effingham County that serves as a residential and community hub within the greater Savannah metropolitan region.
  • E. Fair Oaks, Georgia
    Fair Oaks, Georgia is a small unincorporated community and census-designated place in the Atlanta metropolitan area.
  • 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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e675e3df68819096fb859bc92a0da1 completed April 20, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a086945247c8190bde18a3f9c80ea7c completed May 16, 2026, 12:55 p.m.
Created at: April 16, 2026, 10:32 a.m.