Triple

T14194654
Position Surface form Disambiguated ID Type / Status
Subject Beachton, Georgia E351803 entity
Predicate county P75 FINISHED
Object Grady County E650576 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: Grady County | Statement: [Beachton, Georgia, county, Grady County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grady County
Context triple: [Beachton, Georgia, county, Grady County]
  • A. Grady County chosen
    Grady County is a rural county in southwestern Georgia, United States, known for its agricultural economy and for having Cairo as its county seat.
  • B. Grady County
    Grady County is a county in central Oklahoma known for its agricultural economy and communities such as Chickasha.
  • C. Treutlen County
    Treutlen County is a rural county in east-central Georgia, known for its small population, agricultural landscape, and county seat of Soperton.
  • D. Lumpkin County
    Lumpkin County is a county in northern Georgia known historically as a center of the Georgia Gold Rush and for its location in the Appalachian foothills.
  • E. Choctaw County
    Choctaw County is a rural county in southwestern Alabama known for its pine forests, timber industry, and small, close-knit communities.
  • 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_69d827894ac0819097803e57f3227b23 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61e1fbd48190a4864fa4443f8f29 completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cd12c308190ac868ffe7c5539b0 completed May 8, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:04 a.m.