Triple

T5506839
Position Surface form Disambiguated ID Type / Status
Subject Chippewa Township E144460 entity
Predicate county P75 FINISHED
Object Beaver County E20430 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: [Chippewa Township, county, Beaver County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beaver County
Context triple: [Chippewa Township, county, Beaver County]
  • A. Beaver County chosen
    Beaver County is a county in western Pennsylvania that forms part of the greater Pittsburgh metropolitan area.
  • B. Beaver County
    Beaver County is a rural county in southwestern Utah known for its mountainous terrain, outdoor recreation, and the county seat of Beaver.
  • 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. Park County
    Park County is a rural county in southwestern Montana known for its proximity to Yellowstone National Park and its scenic mountain landscapes.
  • E. Adams County
    Adams County is a largely rural county in eastern Washington State known for its agricultural production, particularly wheat and potatoes.
  • 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_69c008f6b5048190a09064116062cf69 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f47d2dc8190ad874be6902d8a4c completed March 22, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027bc39208190baa01feadb75d3c6 completed March 22, 2026, 5:32 p.m.
Created at: March 22, 2026, 3:32 p.m.