Triple

T21323101
Position Surface form Disambiguated ID Type / Status
Subject Russell County, Virginia E525672 entity
Predicate hasSettlement P1068 FINISHED
Object Lebanon, Virginia 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: Lebanon, Virginia | Statement: [Russell County, Virginia, hasSettlement, Lebanon, Virginia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lebanon, Virginia
Context triple: [Russell County, Virginia, hasSettlement, Lebanon, Virginia]
  • A. Lebanon, Virginia chosen
    Lebanon, Virginia is a small town in southwestern Virginia that serves as the administrative and commercial hub of Russell County.
  • B. Wilson, Virginia
    Wilson, Virginia is an unincorporated rural community located in Dinwiddie County in the Commonwealth of Virginia.
  • C. Louisa, Virginia
    Louisa, Virginia is a small historic town in central Virginia that serves as the county seat of Louisa County.
  • D. Pound, Virginia
    Pound, Virginia is a small Appalachian town in southwestern Virginia known for its coal-mining heritage and location near the Kentucky border.
  • E. Marshall, Virginia
    Marshall, Virginia is a small unincorporated community and historic village in Fauquier County known for its rural character and proximity to the Blue Ridge Mountains.
  • 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_69e0b51ad810819098c12392c8e55f6c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e77ed572548190bd71ef690fc7befe completed April 21, 2026, 1:42 p.m.
Created at: April 16, 2026, 4:40 p.m.