Triple

T996887
Position Surface form Disambiguated ID Type / Status
Subject Johnston County E21514 entity
Predicate borderedBy P224 FINISHED
Object Wayne County E107679 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: Wayne County | Statement: [Johnston County, borderedBy, Wayne County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wayne County
Context triple: [Johnston County, borderedBy, Wayne County]
  • A. Wayne County
    Wayne County is a populous county in southeastern Michigan that includes the city of Detroit and serves as a major industrial and cultural hub of the state.
  • B. Wayne County chosen
    Wayne County is a county in southeastern Georgia known for its rural communities, forestry, and transportation routes connecting coastal and inland parts of the state.
  • C. Madison County
    Madison County is a county in northern Alabama that includes the city of Huntsville, a major center for aerospace, defense, and technology.
  • D. Madison County
    Madison County is a county in central Mississippi, located in the Jackson metropolitan area and known for its rapidly growing suburban communities.
  • E. Warren County
    Warren County is a county in northeastern New York State known for encompassing much of the Adirondack Mountains and popular tourist destinations such as Lake George.
  • 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_69a493c476b48190b41fc5e793171cc6 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4e0f0d081908b888c246d001786 completed March 1, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69adf3a5cac081908d655e42a58a81c5 completed March 8, 2026, 10:09 p.m.
Created at: March 1, 2026, 7:41 p.m.