Triple

T6239298
Position Surface form Disambiguated ID Type / Status
Subject Broken Arrow, Oklahoma E139558 entity
Predicate county P75 FINISHED
Object Wagoner County E281083 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: Wagoner County | Statement: [Broken Arrow, Oklahoma, county, Wagoner County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wagoner County
Context triple: [Broken Arrow, Oklahoma, county, Wagoner County]
  • A. Wagoner County chosen
    Wagoner County is a county in northeastern Oklahoma that includes part of the city of Broken Arrow and is part of the Tulsa metropolitan area.
  • B. Garvin County
    Garvin County is a county in south-central Oklahoma known for its agricultural economy, small towns, and location within the state's oil and gas region.
  • C. Bonner County
    Bonner County is a largely rural county in northern Idaho known for its forests, lakes, and outdoor recreation areas, including parts of Lake Pend Oreille and the Selkirk Mountains.
  • D. Stephens County
    Stephens County is a county in northeastern Georgia, United States, known for its location in the Appalachian foothills and its seat, the city of Toccoa.
  • E. Crane County
    Crane County is a sparsely populated county in western Texas known for its oil production and rural desert landscape.
  • 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_69c008b0e7ac8190808a59573ee646f3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063048df081909a13d16b6f6bf65d completed March 22, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c243ff29248190abbb748601039f60 completed March 24, 2026, 7:57 a.m.
Created at: March 22, 2026, 4:23 p.m.