Triple

T3209955
Position Surface form Disambiguated ID Type / Status
Subject Greenbrier County E67254 entity
Predicate countySeat P383 FINISHED
Object Lewisburg E221659 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: Lewisburg | Statement: [Greenbrier County, countySeat, Lewisburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lewisburg
Context triple: [Greenbrier County, countySeat, Lewisburg]
  • A. Lewisburg, West Virginia chosen
    Lewisburg, West Virginia is a small historic city in Greenbrier County known for its preserved 18th- and 19th-century architecture, cultural events, and proximity to the Greenbrier Valley.
  • B. Yatesville
    Yatesville is a small town located in the U.S. state of Georgia.
  • C. Lastoursville
    Lastoursville is a town in central Gabon known as a regional hub along the Trans-Gabon Railway and for its nearby cave systems and karst landscapes.
  • D. Corryton
    Corryton is an unincorporated community in northeastern Knox County, Tennessee, situated within the Knoxville metropolitan area.
  • E. Brownsville, Pennsylvania
    Brownsville, Pennsylvania is a historic borough along the Monongahela River known for its early role in American westward expansion and riverboat commerce.
  • 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_69ad858ac36c81909962589cd277d6e2 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaab701c48190b91404ab416f7ce3 completed March 8, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2622d4e988190a8a98a0bc9353e3f completed March 12, 2026, 6:50 a.m.
Created at: March 8, 2026, 3:07 p.m.