This sounds reasonable until you see how easily it goes wrong:
NHK ONE ニュース トップ政治ニュース一覧自民税調会長 消費税減税の財源 “租税特別措置見直しなどで”このページを見るにはご利用意向の確認をお願いします。ご利用にあたって。爱思助手下载最新版本对此有专业解读
，更多细节参见搜狗输入法下载
Up to 10 simultaneous connections。关于这个话题，搜狗输入法2026提供了深入分析
一边是“全球最高端、最顶级”的定位，一边是“10万元游艇”的大众化想象，更进一步印证了刘强东对于游艇产业的深入研究和信心笃定。
This does not mean confusables.txt is wrong. It means confusables.txt is a visual-similarity claim that has never been empirically validated at scale. Many entries map characters to the same abstract target under NFKC decomposition (mathematical bold A to A, for instance), and the mapping is semantically correct even if the glyphs look nothing alike. But if you treat every confusables.txt entry as equally dangerous for UI security, you are generating massive false positive rates for 96.5% of the dataset.