Triple

T12235580
Position Surface form Disambiguated ID Type / Status
Subject Lee County, Alabama E291581 entity
Predicate subdivisionName P747 FINISHED
Object Lee County E163376 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: Lee County | Statement: [Lee County, Alabama, subdivisionName, Lee County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lee County
Context triple: [Lee County, Alabama, subdivisionName, Lee County]
  • A. Lee County chosen
    Lee County is a county in eastern Alabama known for being home to the city of Auburn and Auburn University.
  • B. 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.
  • C. Lee County
    Lee County is a county in northern Illinois known for its largely rural landscape, small towns, and agricultural economy.
  • D. 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.
  • E. Lauderdale County
    Lauderdale County is a county in the northwestern part of Alabama, known for its seat in Florence and location along the Tennessee River.
  • 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_69d6ab668acc8190963ba424049d6aee completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cb2892c81909a97b3ad6ec2c21b completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a004f3548b48190aec852723654bd35 completed May 10, 2026, 9:26 a.m.
Created at: April 8, 2026, 9:51 p.m.