feat(normalizer): drop unmatched-names.csv; unresolved-names is the names report

The unmatched list was just non-family correspondents (expected noise);
their count stays in summary.txt and they remain in canonical-persons.xlsx.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

tools/import-normalizer/normalize.py

@@ -83,14 +83,6 @@ def run(*, document_workbook, document_sheet, person_workbook, person_sheet,
     writers.write_review_csv(review_dir / "unparsed-dates.csv",
                              ["raw", "count", "example_rows", "suggested_iso", "suggested_precision"], unparsed_rows)
 
-    unmatched_rows = []
-    for name, rows in sorted(ctx.unmatched.items()):
-        sid, score = alias_index.suggest(name)
-        unmatched_rows.append([name, len(rows), " ".join(map(str, rows[:5])),
-                               sid or "", f"{score:.2f}" if sid else ""])
-    writers.write_review_csv(review_dir / "unmatched-names.csv",
-                             ["raw", "count", "example_rows", "suggested_id", "suggested_score"], unmatched_rows)
-
     writers.write_review_csv(review_dir / "duplicate-index.csv", ["source_row", "index"], duplicates)
     writers.write_review_csv(review_dir / "blank-index-rows.csv", ["source_row", "kind", "content"], blank_index)
     writers.write_review_csv(review_dir / "skipped-x-suffix.csv", ["source_row", "index", "base_index"], skipped_x)