Triple

T13335851
Position Surface form Disambiguated ID Type / Status
Subject Iron County E317689 entity
Predicate borders P224 FINISHED
Object Beaver County E187725 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: Beaver County | Statement: [Iron County, borders, Beaver County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beaver County
Context triple: [Iron County, borders, Beaver County]
  • A. Beaver County chosen
    Beaver County is a rural county in southwestern Utah known for its mountainous terrain, outdoor recreation, and the county seat of Beaver.
  • B. Beaver County
    Beaver County is a county in western Pennsylvania that forms part of the greater Pittsburgh metropolitan area.
  • C. Beaver County
    Beaver County is a sparsely populated county in the Oklahoma Panhandle known for its agricultural economy and wide-open High Plains landscape.
  • D. Clearfield County
    Clearfield County is a largely rural county in central Pennsylvania known for its forests, outdoor recreation, and small communities.
  • E. Park County
    Park County is a rural county in southwestern Montana known for its proximity to Yellowstone National Park and its scenic mountain landscapes.
  • 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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99d00b75c8190af98784c7df904c8 completed April 11, 2026, 12:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f39f298819088d79cda3ac2b375 completed May 3, 2026, 10:11 a.m.
Created at: April 9, 2026, 9:30 p.m.