Triple

T11388798
Position Surface form Disambiguated ID Type / Status
Subject Parker, Arizona E269777 entity
Predicate regionalHubFor P2958 FINISHED
Object La Paz County E594039 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: La Paz County | Statement: [Parker, Arizona, regionalHubFor, La Paz County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Paz County
Context triple: [Parker, Arizona, regionalHubFor, La Paz County]
  • A. La Paz County chosen
    La Paz County is a sparsely populated county in western Arizona known for its desert landscapes, Colorado River recreation areas, and small rural communities.
  • B. Saluda County
    Saluda County is a rural county in central South Carolina known for its agricultural landscape, historic small towns, and outdoor recreation along its rivers and lakes.
  • C. Mayes County
    Mayes County is a county in northeastern Oklahoma known for its mix of small towns, agricultural areas, and recreational lakes.
  • D. Prescott County
    Prescott County was a former county in eastern Ontario, Canada, that later became part of the United Counties of Prescott and Russell.
  • E. Sierra County
    Sierra County is a sparsely populated, mountainous county in northeastern California known for its rugged Sierra Nevada landscapes and historic Gold Rush-era towns.
  • 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_69d6aacdbc6c8190af6dc3d5f5d22836 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7fc389d4c81909515a5c8b0099c36 completed April 9, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5e8cc338081908da977b5b7c6bef3 completed April 20, 2026, 8:50 a.m.
Created at: April 8, 2026, 9:34 p.m.