Triple

T1219212
Position Surface form Disambiguated ID Type / Status
Subject Virginia Range E26178 entity
Predicate region P40 FINISHED
Object Lyon County E26741 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: Lyon County | Statement: [Virginia Range, region, Lyon County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lyon County
Context triple: [Virginia Range, region, Lyon County]
  • A. Lyon County chosen
    Lyon County is a largely rural county in western Nevada known for its historic mining towns and growing residential communities.
  • B. Logan County
    Logan County is a largely rural, coal-mining region in southern West Virginia known for its Appalachian landscape and history.
  • C. 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.
  • D. Lawrence County
    Lawrence County is a county in western Pennsylvania that forms part of the greater Pittsburgh metropolitan region.
  • E. 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.
  • 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_69a4948331fc8190b531ac9bec71c491 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be1d55a08190a138b2411a7c4376 completed March 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69aea82191408190892e9a8e12504a8f completed March 9, 2026, 10:59 a.m.
Created at: March 1, 2026, 7:46 p.m.