{"id":91294,"date":"2026-08-07T15:56:47","date_gmt":"2026-08-07T07:56:47","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/91294.html"},"modified":"2026-08-07T15:56:47","modified_gmt":"2026-08-07T07:56:47","slug":"%e4%bb%8e-seo-%e5%88%b0-geo%e7%94%9f%e6%88%90%e5%bc%8f%e5%bc%95%e6%93%8e%e4%bc%98%e5%8c%96%e7%9a%84%e6%8a%80%e6%9c%af%e6%8b%86%e8%a7%a3%ef%bc%8c%e4%bb%a5%e5%8f%8a%e4%b8%80%e5%a5%97%e5%8f%af%e5%a4%8d","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/91294.html","title":{"rendered":"\u4ece SEO \u5230 GEO\u751f\u6210\u5f0f\u5f15\u64ce\u4f18\u5316\u7684\u6280\u672f\u62c6\u89e3\uff0c\u4ee5\u53ca\u4e00\u5957\u53ef\u590d\u73b0\u7684\u8bc4\u6d4b\u65b9\u6cd5"},"content":{"rendered":"

\u4ece SEO \u5230 GEO<\/p>\n

\u751f\u6210\u5f0f\u5f15\u64ce\u4f18\u5316\u7684\u6280\u672f\u62c6\u89e3，\u4ee5\u53ca\u4e00\u5957\u53ef\u590d\u73b0\u7684\u8bc4\u6d4b\u65b9\u6cd5<\/p>\n

\u8fd9\u4e24\u5e74\u505a\u5185\u5bb9\u548c\u7ad9\u70b9\u7684\u540c\u5b66\u5927\u6982\u90fd\u9047\u5230\u8fc7\u540c\u4e00\u4e2a\u95ee\u9898：\u8d8a\u6765\u8d8a\u591a\u7684\u7528\u6237\u4e0d\u518d\u70b9\u5f00\u641c\u7d22\u7ed3\u679c，\u800c\u662f\u76f4\u63a5\u95ee\u6a21\u578b\u3002\u4e8e\u662f\u300c\u6211\u4eec\u7684\u4ea7\u54c1\u5728 AI \u7684\u56de\u7b54\u91cc\u662f\u4ec0\u4e48\u6837\u5b50\u300d\u53d8\u6210\u4e86\u4e00\u4e2a\u9700\u8981\u88ab\u56de\u7b54\u3001\u5374\u5f88\u96be\u91cf\u5316\u7684\u95ee\u9898\u3002<\/p>\n

\u8fd9\u7bc7\u6587\u7ae0\u4e0d\u8c08\u6982\u5ff5\u5305\u88c5，\u53ea\u505a\u4e09\u4ef6\u4e8b：\u62c6\u4e00\u4e0b\u751f\u6210\u5f0f\u5f15\u64ce\u4ea7\u51fa\u7b54\u6848\u7684\u94fe\u8def\u3001\u8bf4\u6e05\u695a\u5de5\u7a0b\u4fa7\u771f\u6b63\u80fd\u52a8\u7684\u51e0\u4e2a\u5730\u65b9\u3001\u7ed9\u4e00\u5957\u80fd\u8dd1\u8d77\u6765\u7684\u8bc4\u6d4b\u9aa8\u67b6，\u5916\u52a0\u4e00\u7ec4\u5b9e\u6d4b\u6570\u636e\u548c\u5b83\u7684\u53e3\u5f84\u8bf4\u660e\u3002\u6587\u672b\u4f1a\u5199\u6e05\u695a\u8fd9\u5957\u65b9\u6cd5\u7684\u5c40\u9650\u3002<\/p>\n

\u5229\u76ca\u76f8\u5173：\u672c\u6587\u7b2c\u4e09\u7ae0\u7684\u6307\u6807\u53e3\u5f84\u4e0e\u8bc4\u6d4b\u9aa8\u67b6\u3001\u7b2c\u56db\u7ae0\u7684\u5b9e\u6d4b\u6570\u636e，\u90fd\u6765\u81ea\u542f\u822a\u521b\u670d InnoLyceum AI（https:\/\/innolyceum.com\/platform）\u7684\u5b9e\u9645\u9879\u76ee，\u4f5c\u8005\u53c2\u4e0e\u5176\u4e2d\u3002\u6587\u4e2d\u4e0d\u542b\u4ea7\u54c1\u529f\u80fd\u4ecb\u7ecd；\u539f\u59cb\u6837\u672c\u56e0\u5ba2\u6237\u4fdd\u5bc6\u4e0d\u516c\u5f00，\u6280\u672f\u7ed3\u8bba\u8bf7\u7ed3\u5408\u7b2c\u516d\u7ae0\u7684\u5c40\u9650\u81ea\u884c\u590d\u6838\u3002<\/p>\n

\u4e00\u3001GEO \u4e0d\u662f\u300c\u6362\u4e86\u4e2a\u540d\u5b57\u7684 SEO\u300d<\/p>\n

GEO（Generative Engine Optimization，\u751f\u6210\u5f0f\u5f15\u64ce\u4f18\u5316）\u5e38\u88ab\u5f53\u6210 SEO \u7684\u65b0\u9a6c\u7532\u3002\u4f46\u53ea\u8981\u628a\u4e24\u8005\u7684\u4ea7\u51fa\u94fe\u8def\u753b\u51fa\u6765，\u5c31\u4f1a\u53d1\u73b0\u4f18\u5316\u5bf9\u8c61\u6839\u672c\u4e0d\u662f\u4e00\u4e2a\u4e1c\u897f\u3002<\/p>\n

\u4f20\u7edf\u641c\u7d22\u5f15\u64ce\u5927\u81f4\u662f：<\/p>\n

query \u2192 \u67e5\u8be2\u7406\u89e3 \u2192 \u5012\u6392\u7d22\u5f15\u53ec\u56de \u2192 \u6392\u5e8f \u2192 \u8fd4\u56de\u94fe\u63a5\u5217\u8868 \u2192 \u7528\u6237\u81ea\u5df1\u7b5b\u9009<\/p>\n

\u751f\u6210\u5f0f\u5f15\u64ce（\u542b\u5e26\u68c0\u7d22\u7684\u5bf9\u8bdd\u4ea7\u54c1\u3001\u7b54\u6848\u5f15\u64ce\u3001\u641c\u7d22\u91cc\u7684 AI \u6458\u8981）\u5927\u81f4\u662f：<\/p>\n

query \u2192 \u610f\u56fe\u7406\u89e3 \/ \u67e5\u8be2\u6539\u5199（\u5e38\u62c6\u6210\u591a\u6761\u5b50\u67e5\u8be2）
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u2192 \u68c0\u7d22（\u6a21\u578b\u5185\u90e8\u77e5\u8bc6 + \u8054\u7f51\u68c0\u7d22 + \u7ad9\u5185\u7d22\u5f15）
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u2192 \u7247\u6bb5\u53ec\u56de\u4e0e\u91cd\u6392（chunk \u7ea7，\u4e0d\u662f\u9875\u9762\u7ea7）
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u2192 \u5f52\u7eb3\u5408\u6210 \u2192 \u8f93\u51fa\u4e00\u4e2a\u7b54\u6848（\u53ef\u80fd\u9644\u5f15\u7528）<\/p>\n

\u56db\u4e2a\u5dee\u5f02\u5bf9\u5de5\u7a0b\u5b9e\u8df5\u7684\u5f71\u54cd\u6700\u76f4\u63a5：<\/p>\n

1）\u4ea7\u51fa\u662f\u4e00\u4e2a\u7b54\u6848，\u4e0d\u662f\u4e00\u9875\u94fe\u63a5\u3002\u00a0\u300c\u7b2c\u51e0\u540d\u300d\u7684\u542b\u4e49\u53d8\u4e86\u3002\u5728\u4e00\u4e2a\u53ea\u5217 3 \u5230 5 \u4e2a\u5019\u9009\u7684\u7b54\u6848\u91cc，\u7b2c 6 \u540d\u548c\u4e0d\u5b58\u5728\u6ca1\u6709\u533a\u522b\u3002<\/p>\n

2）\u53ec\u56de\u5355\u4f4d\u662f\u7247\u6bb5（chunk），\u4e0d\u662f\u9875\u9762\u3002\u00a0\u68c0\u7d22\u4fa7\u901a\u5e38\u628a\u6b63\u6587\u5207\u6210\u51e0\u767e token \u7684\u5757\u518d\u505a\u5411\u91cf／\u5173\u952e\u8bcd\u6df7\u5408\u53ec\u56de\u3002\u4e00\u4e2a\u5199\u5f97\u5f88\u597d\u4f46\u7ed3\u8bba\u57cb\u5728\u7b2c 8 \u6bb5\u7684\u9875\u9762，\u5f88\u53ef\u80fd\u6574\u7bc7\u90fd\u53ec\u4e0d\u56de\u6765\u3002\u53ef\u6458\u5f55\u6027\u5f00\u59cb\u6bd4\u5173\u952e\u8bcd\u5bc6\u5ea6\u91cd\u8981\u3002<\/p>\n

3）\u5f15\u7528\u6765\u6e90\u662f\u88ab\u663e\u5f0f\u6311\u9009\u7684\u3002\u00a0\u7b54\u6848\u5f15\u64ce\u4f1a\u6311\u51e0\u6761\u5b83\u8ba4\u4e3a\u53ef\u4fe1\u3001\u53ef\u6838\u9a8c\u7684\u6765\u6e90\u3002\u4fe1\u6e90\u7ed3\u6784（\u81ea\u6709\u7ad9\u70b9\u3001\u7b2c\u4e09\u65b9\u5a92\u4f53\u3001\u767e\u79d1／\u699c\u5355／\u95ee\u7b54\u7c7b\u5165\u53e3）\u76f4\u63a5\u51b3\u5b9a\u4e86\u4f60\u6709\u6ca1\u6709\u8d44\u683c\u8fdb\u5165\u5f15\u7528\u5217\u8868\u3002<\/p>\n

4）\u8f93\u51fa\u6709\u968f\u673a\u6027\u3002\u00a0\u91c7\u6837\u6e29\u5ea6\u3001\u6a21\u578b\u7248\u672c\u3001\u68c0\u7d22\u65f6\u5e8f\u3001\u662f\u5426\u8054\u7f51，\u90fd\u4f1a\u8ba9\u540c\u4e00\u4e2a\u95ee\u9898\u5728\u4e0d\u540c\u65f6\u523b\u5f97\u5230\u4e0d\u540c\u7b54\u6848\u3002\u8fd9\u610f\u5473\u7740\u5355\u6b21\u622a\u56fe\u4e0d\u80fd\u4f5c\u4e3a\u4efb\u4f55\u7ed3\u8bba\u7684\u8bc1\u636e\u2014\u2014\u8fd9\u4e00\u70b9\u540e\u9762\u4f1a\u53cd\u590d\u63d0\u5230\u3002<\/p>\n

\u4e8c\u3001\u5de5\u7a0b\u4fa7\u771f\u6b63\u80fd\u52a8\u7684\u56db\u4ef6\u4e8b<\/p>\n

2.1 \u5148\u786e\u8ba4\u722c\u866b\u8fdb\u5f97\u6765<\/p>\n

\u8fd9\u662f\u6700\u5bb9\u6613\u88ab\u5ffd\u7565\u3001\u6210\u672c\u53c8\u6700\u4f4e\u7684\u4e00\u6b65\u3002\u5f88\u591a\u7ad9\u70b9\u7684\u00a0robots.txt\u00a0\u662f\u51e0\u5e74\u524d\u914d\u7684，\u628a AI \u76f8\u5173 UA \u5168\u6321\u5728\u5916\u9762\u800c\u4e0d\u81ea\u77e5\u3002<\/p>\n

\u9700\u8981\u5148\u5206\u6e05\u4e09\u7c7b UA，\u7528\u9014\u5b8c\u5168\u4e0d\u540c（\u4ee5\u5404\u5382\u5546\u516c\u5f00\u6587\u6863\u4e3a\u51c6）：<\/p>\n\n\n\u7c7b\u522b\u4f5c\u7528\u4ee3\u8868 UA<\/tr>\n\n\n\n
\u8bad\u7ec3\u6293\u53d6<\/td>\n\u91c7\u96c6\u8bed\u6599\u7528\u4e8e\u6a21\u578b\u8bad\u7ec3<\/td>\nGPTBot\u3001ClaudeBot\u3001meta-externalagent（\u517c\u505a\u5185\u5bb9\u7d22\u5f15）<\/td>\n<\/tr>\n
\u68c0\u7d22\u6293\u53d6<\/td>\n\u4e3a\u7b54\u6848\u5f15\u64ce\u5efa\u7acb\u7d22\u5f15，\u51b3\u5b9a\u4f60\u80fd\u5426\u88ab\u68c0\u7d22\u5230<\/td>\nOAI-SearchBot\u3001Claude-SearchBot\u3001PerplexityBot\u3001Meta-WebIndexer<\/td>\n<\/tr>\n
\u7528\u6237\u5b9e\u65f6\u53d6\u7528<\/td>\n\u7528\u6237\u5f53\u573a\u8981\u6c42\u6253\u5f00\u67d0\u4e2a\u94fe\u63a5\u65f6\u7684\u6293\u53d6<\/td>\nChatGPT-User\u3001Claude-User\u3001Perplexity-User\u3001meta-externalfetcher<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u53e6\u5916\u8fd8\u6709\u00a0CCBot（Common Crawl）\u3002\u5b83\u5c5e\u4e8e\u975e\u8425\u5229\u7684\u5f00\u653e\u7f51\u9875\u5b58\u6863\u9879\u76ee，\u672c\u8eab\u4e0d\u662f\u67d0\u5bb6\u5382\u5546\u7684\u8bad\u7ec3\u722c\u866b，\u4f46\u4ea7\u51fa\u7684\u8bed\u6599\u88ab\u5927\u91cf\u6a21\u578b\u7528\u4e8e\u8bad\u7ec3，\u653e\u884c\u4e0e\u5426\u9700\u8981\u5355\u72ec\u5224\u65ad\u3002<\/p>\n

\u5982\u679c\u4f60\u7684\u76ee\u6807\u662f\u300c\u88ab AI \u68c0\u7d22\u5230\u5e76\u5f15\u7528\u300d，\u90a3\u4e48\u81f3\u5c11\u8981\u653e\u884c\u7b2c\u4e8c\u7c7b\u3002\u53ea\u653e\u884c\u8bad\u7ec3\u7c7b\u800c\u6321\u4f4f\u68c0\u7d22\u7c7b，\u662f\u5f88\u5e38\u89c1\u7684\u914d\u7f6e\u9519\u8bef\u3002<\/p>\n

\u4e00\u4efd\u6700\u5c0f\u914d\u7f6e：<\/p>\n

# \u68c0\u7d22\u6293\u53d6：\u51b3\u5b9a\u80fd\u5426\u8fdb\u5165\u7b54\u6848\u5f15\u64ce\u7684\u7d22\u5f15
\nUser-agent: OAI-SearchBot
\nDisallow: \/admin\/
\nDisallow: \/api\/
\nAllow: \/
\n\u00a0
\nUser-agent: Claude-SearchBot
\nDisallow: \/admin\/
\nDisallow: \/api\/
\nAllow: \/
\n\u00a0
\nUser-agent: PerplexityBot
\nDisallow: \/admin\/
\nDisallow: \/api\/
\nAllow: \/
\n\u00a0
\n# \u7528\u6237\u5b9e\u65f6\u53d6\u7528
\nUser-agent: ChatGPT-User
\nAllow: \/
\n\u00a0
\nUser-agent: Claude-User
\nAllow: \/
\n\u00a0
\n# \u8bad\u7ec3\u6293\u53d6：\u6309\u81ea\u8eab\u7248\u6743\u7b56\u7565\u51b3\u5b9a\u653e\u884c\u4e0e\u5426
\nUser-agent: GPTBot
\nAllow: \/
\n\u00a0
\nUser-agent: ClaudeBot
\nAllow: \/
\n\u00a0
\n# Google-Extended \u4e0d\u662f\u722c\u866b，\u800c\u662f\u4e00\u4e2a robots.txt \u63a7\u5236\u4ee4\u724c：
\n# \u53ea\u5f71\u54cd Gemini \u7684\u8bad\u7ec3\u4e0e\u63a5\u5730\u7528\u9014，\u4e0d\u5f71\u54cd Googlebot，\u4e5f\u4e0d\u4f5c\u4e3a\u641c\u7d22\u6392\u540d\u4fe1\u53f7
\nUser-agent: Google-Extended
\nAllow: \/
\n\u00a0
\nSitemap: https:\/\/example.com\/sitemap.xml<\/p>\n

\u4e09\u4e2a\u5fc5\u987b\u77e5\u9053\u7684\u524d\u63d0：<\/p>\n

\u2022\u00a0robots.txt\u00a0\u7684 group \u4e0d\u4f1a\u5408\u5e76\u3002\u00a0\u6309 REP，\u4e00\u4e2a bot \u53ea\u5339\u914d\u6700\u5177\u4f53\u7684\u90a3\u4e00\u4e2a group，\u4e0d\u4f1a\u518d\u53bb\u8bfb\u00a0User-agent: *\u00a0\u4e0b\u7684\u89c4\u5219\u3002\u6240\u4ee5\u4f60\u4e00\u65e6\u4e3a\u67d0\u4e2a UA \u5355\u5f00\u4e86 group，\u539f\u6765\u5199\u5728\u00a0*\u00a0\u91cc\u7684\u00a0Disallow: \/admin\/\u3001Disallow: \/api\/\u00a0\u5bf9\u5b83\u5c31\u5168\u90e8\u5931\u6548\u4e86\u2014\u2014\u5fc5\u987b\u5728\u6bcf\u4e2a group \u91cc\u91cd\u6284\u4e00\u904d\u3002\u4e0a\u9762\u7684\u914d\u7f6e\u91cc\u68c0\u7d22\u7c7b UA \u5c31\u662f\u8fd9\u4e48\u5199\u7684\u3002\u8fd9\u662f\u7167\u6284\u914d\u7f6e\u6700\u5bb9\u6613\u8e29\u7684\u5751\u3002<\/p>\n

\u2022\u00a0robots.txt\u00a0\u662f\u541b\u5b50\u534f\u5b9a，\u4e0d\u662f\u8bbf\u95ee\u63a7\u5236\u3002\u00a0\u771f\u8981\u62e6，\u5f97\u5728 WAF／\u7f51\u5173\u5c42\u6309 UA \u548c IP \u6bb5\u505a（\u591a\u6570\u5382\u5546\u4e5f\u63d0\u4f9b IP \u6bb5\u6216 rDNS \u53cd\u67e5\u7528\u4e8e\u6821\u9a8c）\u3002<\/p>\n

\u2022\u00a0\u300c\u7528\u6237\u5b9e\u65f6\u53d6\u7528\u300d\u4e0d\u7b49\u4e8e\u90fd\u5b88 robots\u3002\u00a0OpenAI \u5bf9\u00a0ChatGPT-User\u00a0\u7684\u8bf4\u6cd5\u662f\u300c\u7531\u7528\u6237\u53d1\u8d77，robots.txt \u89c4\u5219\u53ef\u80fd\u4e0d\u9002\u7528\u300d；Perplexity \u5bf9\u00a0Perplexity-User\u00a0\u5199\u7684\u662f\u300c\u4e00\u822c\u4f1a\u5ffd\u7565 robots.txt\u300d；Meta \u5bf9\u00a0meta-externalfetcher\u00a0\u5199\u7684\u662f\u300c\u53ef\u80fd\u7ed5\u8fc7 robots.txt\u300d\u3002\u4f5c\u4e3a\u5bf9\u7167，Anthropic \u6587\u6863\u660e\u786e\u58f0\u660e\u4e09\u4e2a Claude bot（\u542b\u00a0Claude-User）\u5747\u9075\u5b88 robots.txt\u3002\u6240\u4ee5\u522b\u6307\u671b\u9760 robots \u5b9e\u73b0\u4e25\u683c\u7684\u5185\u5bb9\u8fb9\u754c\u3002<\/p>\n

2.2 \u7528\u7ed3\u6784\u5316\u6570\u636e\u964d\u4f4e\u5b9e\u4f53\u6d88\u6b67\u6210\u672c<\/p>\n

\u6a21\u578b\u8981\u56de\u7b54\u300c\u8fd9\u5bb6\u516c\u53f8\u662f\u8c01\u3001\u505a\u4ec0\u4e48\u300d，\u6700\u7701\u529b\u7684\u8def\u5f84\u662f\u76f4\u63a5\u8bfb\u5230\u7ed3\u6784\u5316\u5b57\u6bb5，\u800c\u4e0d\u662f\u4ece\u6563\u6587\u91cc\u731c\u3002JSON-LD \u7684\u8fb9\u9645\u6210\u672c\u6781\u4f4e，\u503c\u5f97\u9ed8\u8ba4\u90e8\u7f72：<\/p>\n

<script type="application\/ld+json">
\n{
\n\u00a0\u00a0"@context": "https:\/\/schema.org",
\n\u00a0\u00a0"@type": "Organization",
\n\u00a0\u00a0"name": "\u793a\u4f8b\u79d1\u6280",
\n\u00a0\u00a0"url": "https:\/\/example.com",
\n\u00a0\u00a0"foundingDate": "2019-03-01",
\n\u00a0\u00a0"description": "\u9762\u5411\u5236\u9020\u4e1a\u7684\u8bbe\u5907\u9884\u6d4b\u6027\u7ef4\u62a4\u8f6f\u4ef6\u4f9b\u5e94\u5546\u3002",
\n\u00a0\u00a0"areaServed": "CN",
\n\u00a0\u00a0"sameAs": [
\n\u00a0\u00a0\u00a0\u00a0"https:\/\/www.wikidata.org\/wiki\/Q00000000",
\n\u00a0\u00a0\u00a0\u00a0"https:\/\/github.com\/example-tech"
\n\u00a0\u00a0]
\n}
\n<\/script><\/p>\n

\u914d\u5408\u00a0FAQPage\u00a0\u5c24\u5176\u503c\u5f97\u505a\u2014\u2014\u5b83\u5929\u7136\u5c31\u662f\u300c\u95ee\u9898 + \u77ed\u7b54\u6848\u300d\u7684\u5f62\u6001，\u548c\u7247\u6bb5\u53ec\u56de\u7684\u7c92\u5ea6\u5b8c\u5168\u5bf9\u9f50：<\/p>\n

<script type="application\/ld+json">
\n{
\n\u00a0\u00a0"@context": "https:\/\/schema.org",
\n\u00a0\u00a0"@type": "FAQPage",
\n\u00a0\u00a0"mainEntity": [{
\n\u00a0\u00a0\u00a0\u00a0"@type": "Question",
\n\u00a0\u00a0\u00a0\u00a0"name": "\u9884\u6d4b\u6027\u7ef4\u62a4\u7cfb\u7edf\u7684\u90e8\u7f72\u5468\u671f\u4e00\u822c\u591a\u4e45？",
\n\u00a0\u00a0\u00a0\u00a0"acceptedAnswer": {
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0"@type": "Answer",
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0"text": "\u6807\u51c6\u90e8\u7f72 6 \u5230 8 \u5468：\u63a5\u5165 2 \u5468\u3001\u51b7\u542f\u52a8 3 \u5468\u3001\u9a8c\u6536 1 \u5468\u3002"
\n\u00a0\u00a0\u00a0\u00a0}
\n\u00a0\u00a0}]
\n}
\n<\/script><\/p>\n

\u5173\u4e8e\u8fd9\u4e24\u6bb5，\u6709\u4e24\u70b9\u63d0\u9192：<\/p>\n

\u2022\u00a0Google \u5df2\u7ecf\u4e0d\u518d\u5c55\u793a FAQ \u5bcc\u7ed3\u679c\u4e86，\u6240\u4ee5\u8fd9\u91cc\u7684\u6536\u76ca\u6307\u5411 AI \u68c0\u7d22\u4fa7\u7684\u7247\u6bb5\u5bf9\u9f50，\u522b\u6307\u671b SERP \u5bcc\u5a92\u4f53\u3002\u53e6\u5916\u7ed3\u6784\u5316\u6570\u636e\u653f\u7b56\u8981\u6c42\u95ee\u7b54\u5185\u5bb9\u5728\u9875\u9762\u4e0a\u5bf9\u7528\u6237\u53ef\u89c1，\u53ea\u57cb JSON-LD \u4e0d\u663e\u793a\u5c5e\u4e8e\u8fdd\u89c4\u7528\u6cd5\u3002<\/p>\n

\u2022\u00a0sameAs\u00a0\u7684\u4f5c\u7528\u662f\u5b9e\u4f53\u5bf9\u9f50：\u628a\u300c\u7ad9\u4e0a\u8fd9\u4e2a\u540d\u5b57\u300d\u548c\u300c\u5916\u90e8\u6743\u5a01\u9875\u9762\u4e0a\u7684\u90a3\u4e2a\u5b9e\u4f53\u300d\u7ed1\u5b9a，\u6709\u52a9\u4e8e\u964d\u4f4e\u540c\u540d\u4f01\u4e1a\u88ab\u5f20\u51a0\u674e\u6234\u7684\u6982\u7387\u3002\u524d\u63d0\u662f\u8fd9\u4e9b URL \u5fc5\u987b\u771f\u5b9e\u5b58\u5728\u4e14\u786e\u5b9e\u6307\u5411\u4f60\u2014\u2014\u7f16\u9020\u6216\u6307\u5411\u4e0d\u5b58\u5728\u7684\u9875\u9762\u53ea\u4f1a\u5236\u9020\u566a\u58f0\u3002\u6ca1\u6709 Wikidata \u6761\u76ee\u5c31\u7528\u5de5\u5546\u516c\u793a\u9875\u3001GitHub \u7ec4\u7ec7\u9875\u6216\u6743\u5a01\u76ee\u5f55\u9875，\u4e0d\u5fc5\u786c\u51d1\u3002<\/p>\n

2.3 \u628a\u6b63\u6587\u5199\u6210\u300c\u53ef\u6458\u5f55\u300d\u7684\u5f62\u72b6<\/p>\n

\u8fd9\u4e00\u8282\u6ca1\u6709\u4ee3\u7801，\u4f46\u5bf9\u53ec\u56de\u7387\u7684\u5f71\u54cd\u53ef\u80fd\u662f\u6700\u5927\u7684\u3002\u65e2\u7136\u53ec\u56de\u5355\u4f4d\u662f chunk，\u6b63\u6587\u5c31\u8981\u6309 chunk \u53cb\u597d\u7684\u65b9\u5f0f\u7ec4\u7ec7：<\/p>\n

\u2022\u00a0\u4e00\u6bb5\u53ea\u8bb2\u4e00\u4ef6\u4e8b，\u7ed3\u8bba\u524d\u7f6e\u3002\u00a0\u628a\u5224\u65ad\u5199\u5728\u6bb5\u9996，\u8bba\u8bc1\u653e\u540e\u9762\u3002\u88ab\u5207\u8d70\u7684\u90a3\u534a\u6bb5\u81f3\u5c11\u8fd8\u5e26\u7740\u7ed3\u8bba\u3002<\/p>\n

\u2022\u00a0\u4e0d\u8981\u8de8\u6bb5\u7528\u4ee3\u8bcd\u6307\u4ee3\u3002\u00a0\u300c\u5b83\u300d\u300c\u8be5\u65b9\u6848\u300d\u300c\u4e0a\u8ff0\u67b6\u6784\u300d\u5728\u88ab\u5207\u6210\u72ec\u7acb chunk \u4e4b\u540e\u4f1a\u5f7b\u5e95\u5931\u53bb\u6307\u4ee3\u5bf9\u8c61\u3002\u5b81\u53ef\u91cd\u590d\u5b9e\u4f53\u540d\u3002<\/p>\n

\u2022\u00a0\u5173\u952e\u4e8b\u5b9e\u81ea\u5e26\u9650\u5b9a\u8bcd\u3002\u00a0\u4e3b\u4f53 + \u6570\u503c + \u5355\u4f4d + \u65f6\u95f4\u7a97 + \u6765\u6e90，\u5199\u5728\u540c\u4e00\u53e5\u91cc\u3002\u300c\u54cd\u5e94\u65f6\u95f4 200ms\u300d\u4e0d\u5982\u300cv2.3 \u5728\u5355\u673a 8 \u6838\u73af\u5883\u4e0b P99 \u54cd\u5e94\u65f6\u95f4\u4e3a 200ms（2026-03 \u5b9e\u6d4b）\u300d\u3002<\/p>\n

\u2022\u00a0\u8868\u683c\u548c FAQ \u4f18\u5148\u3002\u00a0\u53c2\u6570\u3001\u5bf9\u6bd4\u3001\u8fb9\u754c\u6761\u4ef6\u7528\u8868\u683c；\u5e38\u89c1\u95ee\u9898\u7528\u95ee\u7b54\u7ed3\u6784\u3002\u8fd9\u4e24\u79cd\u5f62\u6001\u7684 chunk \u8fb9\u754c\u6700\u5e72\u51c0\u3002<\/p>\n

\u2022\u00a0\u4e0d\u8981\u5047\u8bbe\u68c0\u7d22\u6293\u53d6\u4f1a\u505a OCR\u3002\u00a0\u53c2\u6570\u8868\u753b\u6210\u56fe，\u7b49\u4e8e\u628a\u5b83\u4ece\u7d22\u5f15\u91cc\u5220\u6389\u3002<\/p>\n

\u2022\u00a0\u6b63\u6587\u522b\u4f9d\u8d56\u5ba2\u6237\u7aef\u6e32\u67d3\u3002\u00a0\u76ee\u524d\u516c\u5f00\u6d4b\u8bd5\u7684\u7ed3\u8bba\u662f，\u4e3b\u6d41 AI \u6293\u53d6\u57fa\u672c\u90fd\u4e0d\u6e32\u67d3 JS\u3002\u9996\u5c4f HTML \u91cc\u62ff\u4e0d\u5230\u6b63\u6587，\u540e\u9762\u7684\u4e00\u5207\u90fd\u65e0\u4ece\u8c08\u8d77\u3002\u81ea\u67e5\u65b9\u5f0f\u662f\u6293\u4e00\u53e5\u6b63\u6587\u539f\u8bdd，\u800c\u4e0d\u662f\u6570\u5b57\u8282\u6570：<\/p>\n

curl -s -A "Mozilla\/5.0 (compatible; OAI-SearchBot\/1.0; +https:\/\/openai.com\/searchbot)" \\\\
\n\u00a0\u00a0\u00a0\u00a0\u00a0https:\/\/your.site\/page | grep -c "\u4f60\u6b63\u6587\u91cc\u7684\u4e00\u53e5\u539f\u8bdd"
\n# \u8fd4\u56de 0 = \u9996\u5c4f HTML \u91cc\u6ca1\u6709\u6b63\u6587，\u9700\u8981 SSR \u6216\u9884\u6e32\u67d3<\/p>\n

2.4 \u5173\u4e8e llms.txt，\u8bf4\u70b9\u5b9e\u8bdd<\/p>\n

llms.txt\u00a0\u662f\u4e00\u4e2a\u793e\u533a\u63d0\u51fa\u7684\u7ea6\u5b9a：\u5728\u7ad9\u70b9\u6839\u76ee\u5f55\u653e\u4e00\u4e2a Markdown \u6587\u4ef6，\u7528\u7ed3\u6784\u5316\u7684\u65b9\u5f0f\u544a\u8bc9\u6a21\u578b\u300c\u8fd9\u4e2a\u7ad9\u70b9\u6709\u4ec0\u4e48\u3001\u91cd\u70b9\u770b\u54ea\u51e0\u9875\u300d\u3002<\/p>\n

# \u793a\u4f8b\u79d1\u6280
\n\u00a0
\n> \u9762\u5411\u5236\u9020\u4e1a\u7684\u8bbe\u5907\u9884\u6d4b\u6027\u7ef4\u62a4\u8f6f\u4ef6\u4f9b\u5e94\u5546\u3002
\n\u00a0
\n## \u6838\u5fc3\u6587\u6863
\n– [\u4ea7\u54c1\u6982\u89c8](https:\/\/example.com\/product): \u529f\u80fd\u8fb9\u754c\u4e0e\u9002\u7528\u4ea7\u7ebf\u7c7b\u578b
\n– [\u90e8\u7f72\u6307\u5357](https:\/\/example.com\/docs\/deploy): \u73af\u5883\u8981\u6c42\u3001\u90e8\u7f72\u5468\u671f\u3001\u9a8c\u6536\u6807\u51c6
\n– [\u5e38\u89c1\u95ee\u9898](https:\/\/example.com\/faq): \u4ef7\u683c\u533a\u95f4\u3001\u670d\u52a1\u627f\u8bfa\u3001\u6570\u636e\u5408\u89c4
\n\u00a0
\n## \u53ef\u5f15\u7528\u7684\u4e8b\u5b9e
\n– \u6210\u7acb\u65f6\u95f4：2019 \u5e74 3 \u6708
\n– \u6807\u51c6\u90e8\u7f72\u5468\u671f：6\u20138 \u5468<\/p>\n

\u4f46\u5fc5\u987b\u8bf4\u6e05\u695a\u73b0\u72b6：\u5b83\u5230\u4eca\u5929\u4ecd\u7136\u662f\u63d0\u6848\u6027\u7684\u793e\u533a\u7ea6\u5b9a，\u4e0d\u662f\u6807\u51c6，\u4e3b\u6d41\u5382\u5546\u6ca1\u6709\u7edf\u4e00\u627f\u8bfa\u652f\u6301\u3002\u00a0\u66f4\u8fdb\u4e00\u6b65，\u5df2\u6709\u516c\u5f00\u7edf\u8ba1\u663e\u793a，\u7edd\u5927\u591a\u6570\u90e8\u7f72\u4e86 llms.txt \u7684\u7ad9\u70b9，\u8fd9\u4e2a\u6587\u4ef6\u51e0\u4e4e\u6536\u4e0d\u5230\u4efb\u4f55\u6293\u53d6\u8bf7\u6c42\u3002\u5b83\u7684\u6210\u672c\u5f88\u4f4e（\u5199\u4e00\u4e2a\u6587\u4ef6），\u505a\u4e86\u4e0d\u4e8f；\u4f46\u628a\u5b83\u5f53\u6210\u6392\u540d\u624b\u6bb5\u5c31\u60f3\u591a\u4e86\u3002\u771f\u6b63\u8d77\u4f5c\u7528\u7684\u8fd8\u662f 2.1 \u5230 2.3 \u90a3\u4e09\u4ef6\u4e8b\u3002<\/p>\n

\u4e09\u3001\u8bc4\u6d4b：\u628a\u300cAI \u91cc\u7684\u8868\u73b0\u300d\u53d8\u6210\u53ef\u590d\u73b0\u7684\u6570\u5b57<\/p>\n

\u8fd9\u4e00\u8282\u662f\u5168\u6587\u91cd\u70b9\u3002\u6ca1\u6709\u8bc4\u6d4b，\u524d\u9762\u6240\u6709\u4f18\u5316\u90fd\u662f\u76f2\u6539\u3002<\/p>\n

3.1 \u4e09\u4e2a\u57fa\u7840\u6307\u6807，\u4e14\u4e92\u4e0d\u66ff\u4ee3<\/p>\n

\u7edd\u5927\u591a\u6570\u5173\u4e8e\u300cAI \u53ef\u89c1\u5ea6\u300d\u7684\u4e89\u8bba，\u6839\u6e90\u662f\u628a\u4e0b\u9762\u51e0\u4ef6\u4e8b\u6df7\u4e3a\u4e00\u8c08：<\/p>\n\n\n\u6307\u6807\u5b9a\u4e49\u56de\u7b54\u4ec0\u4e48\u95ee\u9898<\/tr>\n\n\n\n
\u63d0\u53ca\u7387<\/td>\n\u63d0\u53ca\u76ee\u6807\u54c1\u724c\u7684\u6709\u6548\u95ee\u53e5\u6570 \u00f7 \u6709\u6548\u95ee\u53e5\u6570<\/td>\n\u6a21\u578b\u77e5\u4e0d\u77e5\u9053\u5b83<\/td>\n<\/tr>\n
\u63cf\u8ff0\u51c6\u786e\u5ea6<\/td>\n\u5173\u952e\u4e8b\u5b9e\u5168\u90e8\u6b63\u786e\u7684\u63d0\u53ca\u6570 \u00f7 \u63d0\u53ca\u6570<\/td>\n\u8bf4\u5230\u5b83\u7684\u65f6\u5019\u8bf4\u5bf9\u4e86\u6ca1\u6709<\/td>\n<\/tr>\n
\u5e7b\u89c9\u7387<\/td>\n\u51fa\u73b0\u51ed\u7a7a\u634f\u9020\u4e8b\u5b9e\u7684\u63d0\u53ca\u6570 \u00f7 \u63d0\u53ca\u6570<\/td>\n\u6709\u591a\u5c11\u662f\u7f16\u51fa\u6765\u7684<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u4e09\u70b9\u9700\u8981\u8bf4\u660e：<\/p>\n

\u88ab\u63d0\u53ca\u4e0d\u7b49\u4e8e\u88ab\u63a8\u8350，\u88ab\u63a8\u8350\u4e0d\u7b49\u4e8e\u63cf\u8ff0\u51c6\u786e\u3002\u00a0\u4e00\u4e2a\u63d0\u53ca\u7387 80%\u3001\u51c6\u786e\u5ea6 60% \u7684\u7ed3\u679c，\u6bd4\u63d0\u53ca\u7387 50%\u3001\u51c6\u786e\u5ea6 95% \u8981\u7cdf\u7cd5\u5f97\u591a\u2014\u2014\u524d\u8005\u610f\u5473\u7740\u6a21\u578b\u6b63\u5728\u5927\u89c4\u6a21\u5730\u4f20\u64ad\u5173\u4e8e\u5b83\u7684\u9519\u8bef\u4fe1\u606f\u3002\u53ea\u62a5\u4e00\u4e2a\u6570\u7684\u8bc4\u6d4b\u90fd\u4e0d\u53ef\u4fe1\u3002<\/p>\n

\u51c6\u786e\u5ea6\u548c\u5e7b\u89c9\u7387\u4e0d\u662f\u4e92\u8865\u5173\u7cfb\u3002\u00a0\u4e2d\u95f4\u8fd8\u6709\u4e00\u6bb5\u300c\u6709\u504f\u5dee\u4f46\u672a\u634f\u9020\u300d\u7684\u5730\u5e26：\u4fe1\u606f\u8fc7\u65f6\u3001\u53e3\u5f84\u4e0d\u540c\u3001\u63cf\u8ff0\u4e0d\u5b8c\u6574\u3002\u8fd9\u7c7b\u65e2\u4e0d\u8ba1\u5165\u51c6\u786e，\u4e5f\u4e0d\u8ba1\u5165\u5e7b\u89c9\u3002\u5982\u679c\u4f60\u7684\u4e24\u4e2a\u6307\u6807\u6052\u7b49\u4e8e\u52a0\u8d77\u6765 100%，\u8bf4\u660e\u4f60\u5176\u5b9e\u53ea\u6709\u4e00\u4e2a\u6307\u6807\u3002<\/p>\n

\u4f4d\u6b21\u8fd9\u4e2a\u6307\u6807\u8981\u614e\u7528\u3002\u00a0\u5b83\u53ea\u5728\u7b54\u6848\u786e\u5b9e\u5448\u73b0\u4e3a\u6709\u5e8f\u5019\u9009\u5217\u8868\u65f6\u624d\u6709\u610f\u4e49，\u800c\u4e14\u5f3a\u4f9d\u8d56\u7ade\u54c1\u8868\u7684\u5b8c\u6574\u6027（\u89c1 3.4）\u3002\u672c\u6587\u7684\u5b9e\u6d4b\u90e8\u5206\u56e0\u6b64\u4e0d\u62a5\u4f4d\u6b21\u3002<\/p>\n

3.2 \u6837\u672c\u8bbe\u8ba1\u6bd4\u4ee3\u7801\u91cd\u8981<\/p>\n

\u4e0b\u9762\u56db\u6761\u662f\u5728\u5b9e\u9645\u9879\u76ee\u91cc\u53cd\u590d\u5403\u4e8f\u4e4b\u540e\u624d\u56fa\u5316\u4e0b\u6765\u7684\u786c\u89c4\u5219，\u4efb\u4f55\u4e00\u6761\u7834\u4e86，\u8de8\u671f\u548c\u8de8\u5e73\u53f0\u7684\u5bf9\u6bd4\u5c31\u4e0d\u6210\u7acb：<\/p>\n

1.\u00a0\u95ee\u53e5\u6c60\u8981\u5206\u5c42\u4e14\u7248\u672c\u5316\u3002\u00a0\u6309\u51b3\u7b56\u9636\u6bb5\u5206\u5c42（\u8ba4\u77e5\u7c7b \/ \u6bd4\u8f83\u7c7b \/ \u9a8c\u8bc1\u7c7b \/ \u91c7\u8d2d\u7c7b），\u6bcf\u5c42\u56fa\u5b9a\u6761\u6570\u3002\u95ee\u53e5\u6c60\u4e00\u65e6\u6539\u52a8\u5c31\u662f\u65b0\u7248\u672c，\u65b0\u65e7\u7248\u672c\u7684\u6570\u636e\u4e0d\u80fd\u753b\u5728\u540c\u4e00\u5f20\u8d8b\u52bf\u56fe\u91cc\u3002<\/p>\n

2.\u00a0\u5e73\u53f0\u96c6\u56fa\u5b9a\u3002\u00a0\u4e2d\u9014\u589e\u5220\u5e73\u53f0，\u6c47\u603b\u6307\u6807\u4f1a\u51ed\u7a7a\u8df3\u53d8\u3002<\/p>\n

3.\u00a0\u591a\u8f6e\u91c7\u6837\u3002\u00a0\u751f\u6210\u662f\u968f\u673a\u7684，\u5355\u8f6e\u7ed3\u679c\u6ca1\u6709\u7edf\u8ba1\u610f\u4e49\u3002\u540c\u4e00\u95ee\u53e5\u81f3\u5c11\u8dd1 5\u20137 \u8f6e，\u6307\u6807\u6309\u5168\u90e8\u6709\u6548\u6837\u672c\u6c47\u603b\u3002<\/p>\n

4.\u00a0\u6709\u6548\u6837\u672c\u89c4\u5219\u8981\u9884\u5148\u5b9a\u4e49\u3002\u00a0\u62d2\u7b54\u3001\u8d85\u65f6\u3001\u660e\u663e\u8dd1\u9898\u7684\u54cd\u5e94\u7b97\u4e0d\u7b97\u5206\u6bcd，\u5fc5\u987b\u5728\u8dd1\u4e4b\u524d\u5b9a\u597d，\u4e0d\u80fd\u770b\u5b8c\u7ed3\u679c\u518d\u5b9a\u3002<\/p>\n

3.3 \u4e00\u4e2a\u6700\u5c0f\u53ef\u590d\u73b0\u7684\u8bc4\u6d4b\u9aa8\u67b6<\/p>\n

\u4e0b\u9762\u8fd9\u6bb5\u662f\u4ece\u4e0a\u9762\u63d0\u5230\u7684\u90a3\u5957\u5b9e\u9645\u6d41\u7a0b\u91cc\u7b80\u5316\u51fa\u6765\u7684\u9aa8\u67b6，\u53bb\u6389\u4e86\u5e73\u53f0\u9002\u914d\u5c42\u548c\u5b58\u50a8\u5c42，\u53ef\u4ee5\u76f4\u63a5\u6539\u6539\u7528\u3002\u6838\u5fc3\u4e0d\u5728\u4e8e\u8c03\u7528\u54ea\u5bb6 API，\u800c\u5728\u4e8e\u628a\u53e3\u5f84\u56fa\u5316\u6210\u4ee3\u7801\u3002<\/p>\n

# geo_eval.py \u2014\u2014 \u4e00\u4e2a\u6700\u5c0f\u53ef\u590d\u73b0\u7684 GEO \u8bc4\u6d4b\u9aa8\u67b6
\nfrom __future__ import annotations
\nimport re, time, statistics
\nfrom dataclasses import dataclass, field
\nfrom typing import Iterable, Callable, Literal
\n\u00a0
\n# ———- 1. \u5b9e\u4f53\u4e0e\u89c2\u6d4b ———-
\n\u00a0
\n@dataclass(frozen=True)
\nclass Brand:
\n\u00a0\u00a0\u00a0\u00a0canonical: str
\n\u00a0\u00a0\u00a0\u00a0aliases: tuple[str, …] = () # \u7b80\u79f0\u3001\u82f1\u6587\u540d\u3001\u65e7\u540d\u3001\u5e38\u89c1\u9519\u5199
\n\u00a0
\n\u00a0\u00a0\u00a0\u00a0def pattern(self) -> re.Pattern:
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0names = sorted({self.canonical, *self.aliases}, key=len, reverse=True)
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0return re.compile("|".join(map(re.escape, names)))
\n\u00a0
\n@dataclass
\nclass Observation:
\n\u00a0\u00a0\u00a0\u00a0prompt_id: str
\n\u00a0\u00a0\u00a0\u00a0platform: str
\n\u00a0\u00a0\u00a0\u00a0round_id: int
\n\u00a0\u00a0\u00a0\u00a0answer: str
\n\u00a0\u00a0\u00a0\u00a0ts: float = 0.0 # \u91c7\u6837\u65f6\u523b，\u4e8b\u540e\u590d\u6838\u7684\u951a\u70b9
\n\u00a0\u00a0\u00a0\u00a0meta: dict = field(default_factory=dict) # \u8054\u7f51\u5f00\u5173\u3001\u6a21\u578b\u7248\u672c\u3001\u95ee\u53e5\u6c60\u7248\u672c\u2026
\n\u00a0\u00a0\u00a0\u00a0valid: bool = True # \u62d2\u7b54 \/ \u8dd1\u9898 \u2192 False
\n\u00a0\u00a0\u00a0\u00a0error: str | None = None # \u4f20\u8f93\u5931\u8d25，\u4e0e\u300c\u62d2\u7b54\u300d\u533a\u5206\u5f00
\n\u00a0
\n# ———- 2. \u62bd\u53d6 ———-
\n\u00a0
\n# \u5426\u5b9a\u8bed\u5883\u7684\u7c97\u8fc7\u6ee4\u3002\u6ce8\u610f\u4e0d\u8981\u5355\u6536\u300c\u6ca1\u6709\u300d\u2014\u2014\u300c\u6ca1\u6709\u4e4b\u4e00\u300d\u300c\u6ca1\u6709\u660e\u663e\u77ed\u677f\u300d
\n# \u90fd\u662f\u8912\u4e49\u642d\u914d，\u4f1a\u9020\u6210\u7cfb\u7edf\u6027\u8bef\u6740\u3002
\nNEGATIVE = re.compile(
\n\u00a0\u00a0\u00a0\u00a0r"(\u6ca1\u6709(\u6536\u5f55|\u63d0\u4f9b|\u6d89\u53ca|\u76f8\u5173)|\u4e0d\u5305\u62ec|\u4e0d\u5c5e\u4e8e|\u5e76\u975e|\u672a\u63d0\u4f9b|\u6682\u672a\u6536\u5f55|\u4e0d\u63a8\u8350|\u9664.{0,6}\u4e4b\u5916)"
\n)
\n\u00a0
\ndef mentioned(answer: str, brand: Brand) -> bool:
\n\u00a0\u00a0\u00a0\u00a0"""\u4efb\u4e00\u6b21\u51fa\u73b0\u5904\u4e8e\u975e\u5426\u5b9a\u8bed\u5883，\u5373\u7b97\u4e00\u6b21\u6709\u6548\u63d0\u53ca\u3002"""
\n\u00a0\u00a0\u00a0\u00a0for m in brand.pattern().finditer(answer):
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0window = answer[max(0, m.start() – 24): m.end() + 24]
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0if NEGATIVE.search(window) is None:
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0return True
\n\u00a0\u00a0\u00a0\u00a0return False
\n\u00a0
\ndef rank_of(answer: str, brand: Brand, competitors: Iterable[Brand]) -> int | None:
\n\u00a0\u00a0\u00a0\u00a0"""\u6309\u9996\u6b21\u51fa\u73b0\u987a\u5e8f\u4f30\u7b97\u5019\u9009\u4f4d\u6b21\u3002
\n\u00a0\u00a0\u00a0\u00a0\u53ea\u5728\u7b54\u6848\u786e\u5b9e\u5448\u73b0\u4e3a\u5019\u9009\u5217\u8868\u65f6\u624d\u6709\u610f\u4e49；\u4e14\u53ea\u5728\u4f60\u767b\u8bb0\u7684\u7ade\u54c1\u96c6\u5408\u5185\u6392\u5e8f，
\n\u00a0\u00a0\u00a0\u00a0\u7ade\u54c1\u8868\u4e0d\u5168\u4f1a\u8ba9\u540d\u6b21\u7cfb\u7edf\u6027\u504f\u524d\u3002\u8fd4\u56de None \u8868\u793a\u4e0d\u53c2\u4e0e\u7edf\u8ba1\u3002"""
\n\u00a0\u00a0\u00a0\u00a0hits = []
\n\u00a0\u00a0\u00a0\u00a0for b in (brand, *competitors):
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0m = b.pattern().search(answer)
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0if m:
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0hits.append((m.start(), b.canonical))
\n\u00a0\u00a0\u00a0\u00a0if len(hits) < 2:
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0return None
\n\u00a0\u00a0\u00a0\u00a0hits.sort()
\n\u00a0\u00a0\u00a0\u00a0return [name for _, name in hits].index(brand.canonical) + 1
\n\u00a0
\n# ———- 3. \u6307\u6807 ———-
\n\u00a0
\nVerdict = Literal["accurate", "flawed", "fabricated", "unknown"]
\n# accurate \u5173\u952e\u4e8b\u5b9e\u5168\u5bf9
\n# flawed \u6709\u504f\u5dee\u3001\u8fc7\u65f6\u6216\u4e0d\u5b8c\u6574，\u4f46\u6ca1\u6709\u634f\u9020
\n# fabricated \u51fa\u73b0\u51ed\u7a7a\u634f\u9020\u7684\u4e8b\u5b9e（\u865a\u6784\u6570\u503c \/ \u8d44\u8d28 \/ \u4e1a\u52a1\u7ebf）
\n# unknown \u65e0\u6cd5\u5224\u5b9a，\u4e0d\u8ba1\u5165\u5206\u6bcd
\n\u00a0
\ndef metrics(obs: list[Observation],
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0brand: Brand,
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0judge: Callable[[str], Verdict]) -> dict:
\n\u00a0\u00a0\u00a0\u00a0empty = {"n_valid": 0, "n_mention": 0, "mention_rate": None,
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0"accuracy": None, "hallucination": None}
\n\u00a0\u00a0\u00a0\u00a0valid = [o for o in obs if o.valid and o.error is None]
\n\u00a0\u00a0\u00a0\u00a0if not valid:
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0return empty
\n\u00a0
\n\u00a0\u00a0\u00a0\u00a0hit = [o for o in valid if mentioned(o.answer, brand)]
\n\u00a0\u00a0\u00a0\u00a0judged = [v for v in (judge(o.answer) for o in hit) if v != "unknown"]
\n\u00a0
\n\u00a0\u00a0\u00a0\u00a0return {
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0"n_valid": len(valid),
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0"n_mention": len(hit),
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0"mention_rate": round(len(hit) \/ len(valid), 4),
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0"accuracy": round(sum(v == "accurate" for v in judged) \/ len(judged), 4)
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0if judged else None,
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0"hallucination": round(sum(v == "fabricated" for v in judged) \/ len(judged), 4)
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0if judged else None,
\n\u00a0\u00a0\u00a0\u00a0}
\n\u00a0
\n# ———- 4. \u91c7\u6837 ———-
\n\u00a0
\nROUNDS, RETRIES = 7, 3 # \u751f\u6210\u6709\u968f\u673a\u6027，\u5355\u8f6e\u7ed3\u679c\u6ca1\u6709\u7edf\u8ba1\u610f\u4e49
\n\u00a0
\ndef collect(client, platform: str, prompts, meta: dict) -> list[Observation]:
\n\u00a0\u00a0\u00a0\u00a0out = []
\n\u00a0\u00a0\u00a0\u00a0for p in prompts:
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0for r in range(ROUNDS):
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0for attempt in range(RETRIES):
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0try:
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0out.append(Observation(p.id, platform, r, client.ask(p.text),
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0ts=time.time(), meta=dict(meta)))
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0break
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0except Exception as e:
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0if attempt == RETRIES – 1: # \u4f20\u8f93\u5931\u8d25\u4e0d\u8fdb\u6709\u6548\u6837\u672c\u5206\u6bcd
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0out.append(Observation(p.id, platform, r, "", ts=time.time(),
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0meta=dict(meta), valid=False,
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0error=type(e).__name__))
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0time.sleep(2 ** attempt)
\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0time.sleep(1.0) # \u6309\u5404\u5e73\u53f0\u9650\u6d41\u8c03\u6574
\n\u00a0\u00a0\u00a0\u00a0return out<\/p>\n

client.ask()\u00a0\u5404\u5e73\u53f0\u81ea\u884c\u5c01\u88c5\u5373\u53ef\u3002\u771f\u6b63\u9700\u8981\u957f\u671f\u7ef4\u62a4\u7684\u5176\u5b9e\u662f\u4e09\u6837\u4e1c\u897f：\u522b\u540d\u8868\u3001\u5426\u5b9a\u8bcd\u8868\u3001\u4ee5\u53ca\u00a0judge()\u00a0\u7684\u5224\u5b9a\u89c4\u5219\u2014\u2014\u5b83\u4eec\u51b3\u5b9a\u4e86\u6307\u6807\u7684\u771f\u5b9e\u53ef\u4fe1\u5ea6，\u6bd4\u6a21\u578b\u63a5\u53e3\u7a33\u5b9a\u5f97\u591a\u3002judge()\u00a0\u5efa\u8bae\u4eba\u5de5\u62bd\u68c0，\u6216\u7528\u5e26\u8bc1\u636e\u5e93\u7684\u5224\u522b\u6d41\u7a0b，\u4e0d\u8981\u7528\u53e6\u4e00\u4e2a\u6ca1\u6709\u4e8b\u5b9e\u4f9d\u636e\u7684\u6a21\u578b\u76f4\u63a5\u6253\u5206\u3002<\/p>\n

3.4 \u51e0\u4e2a\u5fc5\u8e29\u7684\u5751<\/p>\n

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\u56db\u3001\u4e00\u7ec4\u5b9e\u6d4b\u89c2\u5bdf<\/p>\n

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\"\"<\/p>\n

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\u8c46\u5305<\/td>\n84%<\/td>\n97%<\/td>\n1%<\/td>\n<\/tr>\n
\u901a\u4e49\u5343\u95ee<\/td>\n79%<\/td>\n96%<\/td>\n1%<\/td>\n<\/tr>\n
\u817e\u8baf\u5143\u5b9d<\/td>\n78%<\/td>\n96%<\/td>\n1%<\/td>\n<\/tr>\n
\u6587\u5fc3\u4e00\u8a00<\/td>\n73%<\/td>\n94%<\/td>\n2%<\/td>\n<\/tr>\n
\u667a\u8c31\u6e05\u8a00<\/td>\n71%<\/td>\n93%<\/td>\n2%<\/td>\n<\/tr>\n
Kimi<\/td>\n68%<\/td>\n92%<\/td>\n3%<\/td>\n<\/tr>\n
DeepSeek<\/td>\n62%<\/td>\n90%<\/td>\n4%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u4e09\u70b9\u503c\u5f97\u6ce8\u610f：<\/p>\n

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1.\u00a0\u53e3\u5f84\u6f02\u79fb\u3002\u00a0\u6362\u4e86\u4e2a\u4eba\u7ef4\u62a4，\u5426\u5b9a\u8bcd\u8868\u6539\u4e86\u3001\u6709\u6548\u6837\u672c\u89c4\u5219\u677e\u4e86，\u8d8b\u52bf\u56fe\u4e0a\u5c31\u4f1a\u51fa\u73b0\u4e00\u4e2a\u6765\u8def\u4e0d\u660e\u7684\u8df3\u53d8\u3002<\/p>\n

2.\u00a0\u95ee\u53e5\u6c60\u7248\u672c\u7ba1\u7406\u3002\u00a0\u4e1a\u52a1\u53d8\u5316\u5fc5\u7136\u8981\u6539\u95ee\u53e5\u3002\u6539\u5b8c\u4e4b\u540e\u5386\u53f2\u6570\u636e\u8fd8\u80fd\u4e0d\u80fd\u5bf9\u6bd4\u3001\u600e\u4e48\u6807\u6ce8\u65ad\u70b9，\u9700\u8981\u673a\u5236\u800c\u4e0d\u662f\u53e3\u5934\u7ea6\u5b9a\u3002<\/p>\n

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\u2022\u00a0\u6709\u9650\u6837\u672c\u4e0d\u7b49\u4e8e\u5168\u5e73\u53f0\u7ed3\u8bba\u3002\u00a0100 \u6761\u95ee\u53e5\u8986\u76d6\u7684\u662f\u4e00\u4e2a\u7279\u5b9a\u884c\u4e1a\u7684\u51b3\u7b56\u573a\u666f，\u6362\u4e2a\u884c\u4e1a\u7ed3\u679c\u53ef\u80fd\u5b8c\u5168\u4e0d\u540c\u3002<\/p>\n

\u2022\u00a0\u5f15\u64ce\u4fa7\u4e0d\u53ef\u63a7\u3002\u00a0\u7d22\u5f15\u4e0e\u5426\u3001\u5f15\u7528\u4e0e\u5426\u3001\u5982\u4f55\u6392\u5e8f，\u51b3\u5b9a\u6743\u5728\u5404\u5e73\u53f0\u3002\u4efb\u4f55\u58f0\u79f0\u80fd\u300c\u4fdd\u8bc1 AI \u6392\u540d\u300d\u300c\u4fdd\u8bc1\u6c38\u4e45\u6536\u5f55\u300d\u7684\u8bf4\u6cd5，\u5728\u6280\u672f\u4e0a\u90fd\u7ad9\u4e0d\u4f4f\u3002<\/p>\n

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