/**
 * @copyright Sister Software
 * @license AGPL-3.0
 * @author Teffen Ellis, et al.
 *
 *   Assemble a balanced (address → country) dataset for the #244 coarse-placer from the v0.5.0
 *   corpus. STRATIFIED: a flat random sample is 94% US+FR, so we sample up to N rows PER country
 *   and union.
 *
 *   Two gotchas this handles:
 *
 *   - DuckDB `USING SAMPLE n ROWS` samples the TABLE, then WHERE filters the sample — so we
 *       filter-THEN-sample in a subquery to get a true per-country sample.
 *   - The corpus val/test shards only carry US/FR/DE, so we draw ALL splits from the rich `train`
 *       shards and do our OWN per-country 80/10/10 split (dedup on raw → no row crosses splits).
 *
 *   Run: `mailwoman placer build-dataset [--per-country 50000]` Output:
 *   `<repo>/data/coarse-placer/{train,val,test}.jsonl` (rows: {raw, country})
 */
/**
 * Options for {@linkcode buildDataset}.
 */
export interface BuildDatasetOptions {
    /**
     * Rows sampled per country. Default 50000.
     */
    perCountry?: number;
    /**
     * Dataset output dir. Default `<repo>/data/coarse-placer`.
     */
    data?: string;
}
/**
 * Result of {@linkcode buildDataset}.
 */
export interface BuildDatasetResult {
    outDir: string;
    train: number;
    val: number;
    test: number;
}
/**
 * Coarse-placer dataset builder — see the module doc.
 */
export declare function buildDataset(options?: BuildDatasetOptions, report?: (line: string) => void): Promise<BuildDatasetResult>;
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