Triple

T946795
Position Surface form Disambiguated ID Type / Status
Subject Beaver County E20430 entity
Predicate borderedBy P224 FINISHED
Object Lawrence County E22128 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: Lawrence County | Statement: [Beaver County, borderedBy, Lawrence County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lawrence County
Context triple: [Beaver County, borderedBy, Lawrence County]
  • A. Lawrence County chosen
    Lawrence County is a county in western Pennsylvania that forms part of the greater Pittsburgh metropolitan region.
  • B. Lawrence County
    Lawrence County is a rural county in northern Alabama known for its agricultural communities, outdoor recreation areas, and proximity to the Tennessee River.
  • C. Marshall County
    Marshall County is a county in northern Alabama known for its scenic location around Lake Guntersville and its mix of small towns and rural communities.
  • D. Logan County
    Logan County is a largely rural, coal-mining region in southern West Virginia known for its Appalachian landscape and history.
  • E. Storey County
    Storey County is a small, historic county in northern Nevada best known for the Comstock Lode mining district and the preserved 19th-century town of Virginia City.
  • 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_69a493b0f2fc81908cd227480a5356a1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3bcad2481908b83575b2fb80d14 completed March 1, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae0a910d808190b20150e864ae9bc2 completed March 8, 2026, 11:47 p.m.
Created at: March 1, 2026, 7:40 p.m.