Triple

T7076404
Position Surface form Disambiguated ID Type / Status
Subject Mount Wheeler E164830 entity
Predicate county P75 FINISHED
Object White Pine County E27343 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: White Pine County | Statement: [Mount Wheeler, county, White Pine County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: White Pine County
Context triple: [Mount Wheeler, county, White Pine County]
  • A. White Pine County chosen
    White Pine County is a sparsely populated county in eastern Nevada known for its mountainous landscapes, outdoor recreation, and Great Basin National Park.
  • B. Puck County
    Puck County is an administrative district in northern Poland’s Pomeranian Voivodeship, located along the Baltic Sea coast and known for its seaside towns and maritime tourism.
  • C. Lincoln County
    Lincoln County is a county-level jurisdiction in the U.S. state of Wisconsin, known for its Northwoods landscapes, outdoor recreation, and communities such as Merrill and Tomahawk.
  • D. Lincoln County
    Lincoln County is a sparsely populated agricultural county in eastern Washington State, known for its wheat farming and rural landscapes.
  • E. Lincoln County
    Lincoln County is a county in North Carolina that forms part of the greater Charlotte metropolitan region.
  • 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_69c6887cbc6c8190bdfac42d940f4d8a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e4ebf4048190bf5d7156817f93a7 completed March 27, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c79468c7688190bf10433f05e77574 completed March 28, 2026, 8:42 a.m.
Created at: March 27, 2026, 2:40 p.m.