Triple

T22623412
Position Surface form Disambiguated ID Type / Status
Subject Opelika City Schools E558348 entity
Predicate county P75 FINISHED
Object Lee 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: Lee County | Statement: [Opelika City Schools, county, Lee County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lee County
Context triple: [Opelika City Schools, county, Lee County]
  • A. Lee County
    Lee County is a county-level jurisdiction in South Carolina known for its rural communities, agriculture, and location in the state’s eastern Midlands region.
  • B. Lee County chosen
    Lee County is a county in eastern Alabama known for being home to the city of Auburn and Auburn University.
  • C. Lee County
    Lee County is a coastal county on Florida’s Gulf Coast known for its beaches, barrier islands, and the city of Fort Myers.
  • D. Lee County
    Lee County is a county in northern Illinois known for its largely rural landscape, small towns, and agricultural economy.
  • E. Thomas County
    Thomas County is a county in southern Georgia, United States, known for its historic city of Thomasville and its blend of agricultural and cultural heritage.
  • 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_69e24545a8e08190bfa7482a2c725ff1 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f16e3b97f8819082ea2b23ff4b2173 completed April 29, 2026, 2:34 a.m.
Created at: April 17, 2026, 3:01 p.m.