Triple

T19041583
Position Surface form Disambiguated ID Type / Status
Subject Turin, Georgia E466015 entity
Predicate county P75 FINISHED
Object Coweta County 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: Coweta County | Statement: [Turin, Georgia, county, Coweta County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Coweta County
Context triple: [Turin, Georgia, county, Coweta County]
  • A. Coweta County chosen
    Coweta County is a county in west-central Georgia, part of the Atlanta metropolitan area, known for its historic communities and growing suburban population.
  • B. Coweta
    Coweta is a small city in northeastern Oklahoma that functions as a suburban community within the greater Tulsa metropolitan area.
  • C. Okfuskee County
    Okfuskee County is a rural county in east-central Oklahoma known for its small communities, including the county seat of Okemah, and its historical ties to Native American nations.
  • D. Cole County
    Cole County was the former name of what is now Union County in the southeastern part of South Dakota.
  • E. McClain County
    McClain County is a county in central Oklahoma that forms part of the greater Oklahoma City metropolitan region.
  • 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_69d8dd0359648190bc2a9202c5cf29d2 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d80118248190af6b4c74df5085ad completed April 20, 2026, 7:38 a.m.
Created at: April 10, 2026, 12:02 p.m.