\u751f\u6210AI\u3067\u6cd5\u4ee4\u6587\u7ae0\u3092\u8981\u7d04\u3057\u3001\u6cd5\u52d9\u306e\u52c9\u5f37\u306b\u4f7f\u3063\u3066\u307f\u305f\uff5c\u5b9f\u8df5\u30b9\u30c6\u30c3\u30d7\u8b1b\u5ea7<\/title>\n <style>\n body { max-width: 900px; margin: 0 auto; font-family: \"Yu Gothic\", YuGothic, sans-serif; background: #f7f7fa; color: #222; }\n h1, h2, h3 { color: #006699; }\n pre, code { background: #eee; padding: 1em; border-radius: 8px; display: block; overflow-x: auto; }\n .step { margin: 2em 0; }\n .graph { margin: 1em 0 2em 0; }\n .tips { background: #e3f6fd; border-left: 4px solid #0096c7; padding: 1em; margin: 2em 0; }\n .footer { margin-top: 4em; padding: 2em 0; border-top: 1px solid #bbb; text-align: center; color: #888; }\n ul,ol { margin: 1em 2em; }\n <\/style>\n<\/head>\n<body>\n\n <div class=\"step\">\n <h2>\u306f\u3058\u3081\u306b\uff1a\u306a\u305c\u6cd5\u4ee4\u6587\u7ae0\u306e\u8981\u7d04\u304c\u91cd\u8981\u304b\uff1f<\/h2>\n <p>\n \u6cd5\u52d9\u3084\u884c\u653f\u3001\u7d4c\u55b6\u306b\u643a\u308f\u308b\u4eba\u306b\u3068\u3063\u3066\u3001\u6cd5\u4ee4\u3084\u898f\u5247\u3092\u6b63\u78ba\u304b\u3064\u52b9\u7387\u7684\u306b\u7406\u89e3\u3059\u308b\u3053\u3068\u306f\u975e\u5e38\u306b\u5927\u5207\u3067\u3059\u3002\u3057\u304b\u3057\u3001\u6cd5\u4ee4\u539f\u6587\u306f\u9577\u304f\u3001\u5c02\u9580\u7528\u8a9e\u304c\u591a\u304f\u3001\u4e00\u8aad\u3057\u3066\u8981\u70b9\u3092\u628a\u63e1\u3059\u308b\u306e\u306f\u56f0\u96e3\u3067\u3059\u3002<b>\u751f\u6210AI\uff08\u5927\u898f\u6a21\u8a00\u8a9e\u30e2\u30c7\u30eb\uff1aLLM\uff09<\/b>\u306f\u3001\u305d\u306e\u81a8\u5927\u306a\u6587\u7ae0\u304b\u3089\u8981\u70b9\u3092\u62bd\u51fa\u3057\u3001\u308f\u304b\u308a\u3084\u3059\u3044\u65e5\u672c\u8a9e\u306b\u8981\u7d04\u3059\u308b\u80fd\u529b\u3092\u6301\u3061\u307e\u3059\u3002\u672c\u7a3f\u3067\u306f\u3001\u300c\u751f\u6210AI\u3092\u7528\u3044\u305f\u6cd5\u4ee4\u8981\u7d04\u300d\u306e\u5b9f\u8df5\u624b\u9806\u3068\u5fdc\u7528\u4f8b\u3092\u3001\u5b9f\u969b\u306ePython\u30b5\u30f3\u30d7\u30eb\u30b3\u30fc\u30c9\u3084\u30b0\u30e9\u30d5\u4ed8\u304d\u3067\u89e3\u8aac\u3057\u307e\u3059\u3002\n <\/p>\n <\/div>\n\n <div class=\"step\">\n <h2>STEP 1\uff1a\u6cd5\u4ee4\u30c7\u30fc\u30bf\u306e\u5165\u624b\u3068\u6574\u7406<\/h2>\n <p>\n \u307e\u305a\u3001\u5bfe\u8c61\u3068\u3059\u308b\u6cd5\u4ee4\u6587\u7ae0\uff08\u4f8b\uff1a<a href=\"https:\/\/www.bunka.go.jp\/seisaku\/chosakuken\/seidokaisetsu\/seminar\/2024\/pdf\/94141401_01.pdf\" target=\"_blank\">\u8457\u4f5c\u6a29\u6cd5<\/a>\u3084\u500b\u4eba\u60c5\u5831\u4fdd\u8b77\u6cd5\u306a\u3069\uff09\u3092\u30cd\u30c3\u30c8\u304b\u3089\u53ce\u96c6\u3057\u307e\u3059\u3002\u65e5\u672c\u306e\u6cd5\u4ee4\u306f\u300ce-Gov\u6cd5\u4ee4\u691c\u7d22\u300d\u3084\u5404\u7701\u5e81\u306e\u516c\u958bPDF\u304b\u3089\u5165\u624b\u53ef\u80fd\u3067\u3059\u3002<br>\n <b>\u30dd\u30a4\u30f3\u30c8\uff1a<\/b> <br>\n \u30fbPDF\u3084HTML\u304b\u3089\u30d7\u30ec\u30fc\u30f3\u30c6\u30ad\u30b9\u30c8\u306b\u5909\u63db\uff08\u4f8b\uff1aPython\u306e<code>pdfplumber<\/code>\u3084<code>BeautifulSoup<\/code>\u5229\u7528\uff09<br>\n \u30fb\u5206\u91cf\u304c\u591a\u3044\u5834\u5408\u3001\u6761\u6587\u3054\u3068\u3084\u7ae0\u3054\u3068\u306b\u5206\u5272\u3059\u308b\u3068\u51e6\u7406\u3057\u3084\u3059\u3044\n <\/p>\n <pre><code>\nimport pdfplumber\n\nwith pdfplumber.open(\"94141401_01.pdf\") as pdf:\n text = ''\n for page in pdf.pages:\n text += page.extract_text() + '\\n'\n\nprint(text[:10000]) # \u5148\u982d10000\u5b57\u3060\u3051\u8868\u793a\n <\/code><\/pre>\n <\/div>\n\n <div class=\"step\">\n <h2>STEP 2\uff1a\u751f\u6210AI\uff08GPT\u306a\u3069\uff09\u306b\u3088\u308b\u8981\u7d04<\/h2>\n <p>\n \u53ce\u96c6\u3057\u305f\u6cd5\u4ee4\u6587\u3092\u751f\u6210AI\u306b\u5165\u529b\u3057\u3001\u8981\u7d04\u3092\u4f9d\u983c\u3057\u307e\u3059\u3002gemini\u3084OpenAI\u306eAPI\u3001\u30ed\u30fc\u30ab\u30ebLLM\uff08llama, GPT4All\u7b49\uff09\u3082\u6d3b\u7528\u3067\u304d\u307e\u3059\u3002<br>\n <b>\u4f8b\uff1aGemini API\uff08Python\uff09<\/b>\n <\/p>\n <pre><code>\nimport google.generativeai as genai\n\n# API\u30ad\u30fc\u306fGoogle Cloud Console\u304b\u3089\u53d6\u5f97\u3057\u3066\u304f\u3060\u3055\u3044\ngenai.configure(api_key=\"YOUR_GEMINI_API_KEY\")\n\n# Gemini\u30e2\u30c7\u30eb\u306e\u6307\u5b9a\uff082025\u5e746\u6708\u6642\u70b9\u306e\u6700\u65b0\u7248\uff09\nmodel = genai.GenerativeModel('gemini-1.5-pro-latest')\n\ndef summarize_law(text):\n prompt = f\"\"\"\u3042\u306a\u305f\u306f\u6cd5\u5f8b\u306b\u8a73\u3057\u3044\u5c02\u9580\u5bb6\u3067\u3059\u3002\n\u6b21\u306e\u6cd5\u4ee4\u6587\u7ae0\u3092\u3001\u5c02\u9580\u7528\u8a9e\u306f\u308f\u304b\u308a\u3084\u3059\u3044\u8a00\u8449\u306b\u8a00\u3044\u63db\u3048\u3066\u7c21\u6f54\u306b\u8981\u7d04\u3057\u3066\u304f\u3060\u3055\u3044\u3002\n\n{text}\n\"\"\"\n response = model.generate_content(prompt)\n return response.text\n\n# \u30b5\u30f3\u30d7\u30eb\uff1a1000\u5b57\u305a\u3064\u5206\u5272\u3057\u3066\u51e6\u7406\nparts = [text[i:i+1000] for i in range(0, len(text), 1000)]\nsummaries = [summarize_law(part) for part in parts]\n\nfor s in summaries:\n print(s)\n\n <\/code><\/pre>\n <div class=\"tips\">\n <b>Tips:<\/b> \u8981\u7d04\u3092\u7e70\u308a\u8fd4\u3059\u3053\u3068\u3067\u3001\u7ae0\u3054\u3068\u3001\u6761\u6587\u3054\u3068\u3001\u5168\u4f53\u3068\u300c\u591a\u6bb5\u968e\u8981\u7d04\u300d\u3082\u53ef\u80fd\u3067\u3059\u3002\u751f\u6210AI\u306b\u306f\u660e\u78ba\u306a\u6307\u793a\uff08\u300c\u91cd\u8981\u306a\u90e8\u5206\u306e\u307f\u300d\u306a\u3069\uff09\u3092\u4e0e\u3048\u308b\u306e\u304c\u30b3\u30c4\u3067\u3059\u3002\n <\/div>\n <\/div>\n\n <div class=\"step\">\n <h2>STEP 3\uff1a\u8981\u7d04\u5185\u5bb9\u306e\u5206\u6790\u3068\u53ef\u8996\u5316\uff08\u30b0\u30e9\u30d5\uff09<\/h2>\n <p>\n \u751f\u6210AI\u306b\u3088\u308b\u8981\u7d04\u306e\u4e2d\u304b\u3089\u300c\u983b\u51fa\u30ad\u30fc\u30ef\u30fc\u30c9\u300d\u3084\u300c\u5404\u7ae0\u30fb\u6761\u6587\u306e\u91cd\u8981\u5ea6\u300d\u306a\u3069\u3092\u7d71\u8a08\u7684\u306b\u6574\u7406\u3057\u3001\u30b0\u30e9\u30d5\u3067\u53ef\u8996\u5316\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<br>\n \u4f8b\u3048\u3070\u3001\u6cd5\u4ee4\u8981\u7d04\u304b\u3089\u300c\u500b\u4eba\u60c5\u5831\u300d\u300c\u7b2c\u4e09\u8005\u63d0\u4f9b\u300d\u300c\u672c\u4eba\u540c\u610f\u300d\u306a\u3069\u306e\u30ef\u30fc\u30c9\u51fa\u73fe\u56de\u6570\u3092\u68d2\u30b0\u30e9\u30d5\u3067\u8868\u793a\u3057\u307e\u3059\u3002\n <\/p>\n <pre><code>\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom collections import Counter\n\nall_summary = '\\n'.join(summaries)\nkeywords = ['\u500b\u4eba\u60c5\u5831', '\u7b2c\u4e09\u8005\u63d0\u4f9b', '\u672c\u4eba\u540c\u610f', '\u76ee\u7684\u5916\u5229\u7528', '\u524a\u9664', '\u5229\u7528\u76ee\u7684']\n\ncounter = {k: all_summary.count(k) for k in keywords}\ndf = pd.DataFrame(list(counter.items()), columns=['Keyword', 'Count'])\n\nplt.bar(df['Keyword'], df['Count'])\nplt.title('\u8981\u7d04\u4e2d\u306e\u4e3b\u8981\u30ad\u30fc\u30ef\u30fc\u30c9\u51fa\u73fe\u6570')\nplt.xlabel('\u30ad\u30fc\u30ef\u30fc\u30c9')\nplt.ylabel('\u51fa\u73fe\u56de\u6570')\nplt.tight_layout()\nplt.show()\n <\/code><\/pre>\n\n <\/div>\n\n <div class=\"step\">\n <h2>STEP 4\uff1a\u6cd5\u52d9\u306e\u5b66\u7fd2\u3084\u5b9f\u52d9\u3078\u306e\u5fdc\u7528\u30a2\u30a4\u30c7\u30a2<\/h2>\n <ul>\n <li>\u6cd5\u4ee4\u8981\u7d04\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306e\u81ea\u4f5c \u2192 \u65b0\u4eba\u7814\u4fee\u30fb\u8cc7\u683c\u8a66\u9a13\u5bfe\u7b56\u306b\u6d3b\u7528<\/li>\n <li>\u6761\u6587\u306e\u300c\u96e3\u6613\u5ea6\u300d\u300c\u91cd\u8981\u5ea6\u300d\u30e9\u30d9\u30eb\u4ed8\u3051 \u2192 \u52c9\u5f37\u306e\u512a\u5148\u9806\u4f4d\u4ed8\u3051<\/li>\n <li>\u30b1\u30fc\u30b9\u5225QA\u751f\u6210 \u2192 \u5177\u4f53\u7684\u306a\u30b7\u30fc\u30f3\u3067\u306e\u6761\u6587\u9069\u7528\u4f8b\u3082AI\u306b\u81ea\u52d5\u751f\u6210\u3055\u305b\u308b<\/li>\n <li>\u5224\u4f8b\u3084\u5b9f\u52d9\u4e8b\u4f8b\u3092\u542b\u3081\u3066\u591a\u6bb5\u7684\u8981\u7d04 \u2192 \u5b9f\u52d9\u8005\u5411\u3051\u30ca\u30ec\u30c3\u30b8\u30d9\u30fc\u30b9\u69cb\u7bc9<\/li>\n <li>\u97f3\u58f0\u5316\u30fb\u30ea\u30b9\u30cb\u30f3\u30b0\u6559\u6750\u5316 \u2192 AI\u306b\u3088\u308b\u8981\u7d04\u3068\u97f3\u58f0\u5408\u6210\u3067\u6642\u77ed\u5b66\u7fd2<\/li>\n <\/ul>\n <div class=\"tips\">\n <b>\u5b9f\u52d9Tips\uff1a<\/b><br>\n \u6cd5\u4ee4\u306f\u6bce\u5e74\u6539\u6b63\u304c\u5165\u308b\u305f\u3081\u3001AI\u8981\u7d04\uff0b\u4eba\u9593\u306e\u6700\u65b0\u30c1\u30a7\u30c3\u30af\u304c\u5927\u5207\u3067\u3059\u3002<br>\n ChatGPT\u3084Google Gemini\u306f\u65e5\u672c\u8a9e\u306b\u3082\u5f37\u304f\u3001\u6587\u7ae0\u8981\u7d04\u30fb\u5206\u985e\u30fb\u4f8b\u793a\u751f\u6210\u306a\u3069\u591a\u7528\u9014\u306b\u4f7f\u3048\u307e\u3059\u3002\n <\/div>\n <\/div>\n\n <div class=\"step\">\n <h2>STEP 5\uff1a\u793e\u4f1a\u7684\u306a\u610f\u7fa9\u3068\u4eca\u5f8c\u306e\u5c55\u671b\uff08\u8003\u5bdf\uff09<\/h2>\n <p>\n \u6cd5\u4ee4\u6587\u7ae0\u3092AI\u3067\u8981\u7d04\u3059\u308b\u6280\u8853\u306f\u3001\u793e\u4f1a\u306e\u30c7\u30b8\u30bf\u30eb\u30fb\u30ac\u30d0\u30ca\u30f3\u30b9\u306e\u57fa\u76e4\u5f37\u5316\u3001\u6cd5\u6559\u80b2\u306e\u52b9\u7387\u5316\u3001\u884c\u653fDX\u63a8\u9032\u306b\u4e0d\u53ef\u6b20\u3068\u306a\u3063\u3066\u304d\u307e\u3057\u305f\u3002<br>\n \u6cd5\u52d9\u5206\u91ce\u3067\u306f\u3001\u3053\u308c\u307e\u3067\u5f01\u8b77\u58eb\u3084\u884c\u653f\u66f8\u58eb\u304c\u6642\u9593\u3092\u304b\u3051\u3066\u8981\u70b9\u6574\u7406\u3057\u3066\u304d\u305f\u4f5c\u696d\u304c\u3001AI\u306b\u3088\u308a\u5927\u5e45\u306b\u81ea\u52d5\u5316\u3055\u308c\u3064\u3064\u3042\u308a\u307e\u3059\u3002\u305d\u306e\u7d50\u679c\u3001\u3088\u308a\u591a\u304f\u306e\u4eba\u304c\u77ed\u6642\u9593\u3067\u6cd5\u7684\u306a\u77e5\u8b58\u306b\u30a2\u30af\u30bb\u30b9\u3067\u304d\u3001\u696d\u52d9\u306e\u52b9\u7387\u5316\u3084\u8aa4\u89e3\u306e\u524a\u6e1b\u306b\u3064\u306a\u304c\u308a\u307e\u3059\u3002<br>\n \u307e\u305f\u3001\u5b98\u6c11\u3067\u306e\u6cd5\u4ee4\u8981\u7d04\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u6574\u5099\u304c\u9032\u3080\u3053\u3068\u3067\u3001AI\u306b\u3088\u308b\u6cd5\u4ee4\u691c\u7d22\u30fb\u81ea\u52d5\u6587\u66f8\u4f5c\u6210\u30fb\u5224\u4f8b\u81ea\u52d5\u5206\u985e\u3068\u3044\u3063\u305f\u65b0\u305f\u306a\u5fdc\u7528\u3082\u5e83\u304c\u308a\u3064\u3064\u3042\u308a\u307e\u3059\u3002\n <\/p>\n <p>\n <b>\u4eca\u5f8c\u306f\u3001\u300c\u6cd5\u4ee4\u30c7\u30fc\u30bf\uff0b\u751f\u6210AI\u300d\u00d7\u300c\u30d3\u30b8\u30e5\u30a2\u30e9\u30a4\u30ba\u300d\u00d7\u300c\u81ea\u7136\u8a00\u8a9eQA\u5316\u300d<\/b>\u304c\u4e00\u822c\u5316\u3057\u3001\u4f01\u696d\u30fb\u81ea\u6cbb\u4f53\u30fb\u6559\u80b2\u73fe\u5834\u3067\u306e\u5c0e\u5165\u304c\u6025\u901f\u306b\u9032\u3080\u3068\u4e88\u60f3\u3055\u308c\u307e\u3059\u3002\n <\/p>\n <\/div>\n\n <div class=\"step\">\n <h2>\u5fdc\u7528\u30d6\u30ed\u30b0\u30cd\u30bf\u30fb\u8da3\u5473\u3078\u306e\u5e83\u304c\u308a\u4f8b<\/h2>\n <ul>\n <li>\u300cChatGPT\u3067\u516d\u6cd5\u5168\u66f8\u3092\u8981\u7d04\u3057\u3066\u307f\u305f\uff01\u77e5\u3089\u306a\u3044\u6761\u6587\u304c\u8eab\u8fd1\u306b\u306a\u308b\u300d<\/li>\n <li>\u300c\u8cc7\u683c\u8a66\u9a13\u306b\u5f79\u7acb\u3064AI\u6cd5\u4ee4\u8981\u7d04\u30ce\u30fc\u30c8\u306e\u4f5c\u308a\u65b9\u300d<\/li>\n <li>\u300c\u81ea\u4f5cAI\u6cd5\u4ee4\u30dc\u30c3\u30c8\u3067\u201c\u79c1\u306e\u305f\u3081\u306e\u30ea\u30fc\u30ac\u30eb\u76f8\u8ac7\u201d\u300d<\/li>\n <li>\u300cOpenAI\uff0bPython\u3067\u30aa\u30ea\u30b8\u30ca\u30eb\u5224\u4f8b\u8f9e\u66f8\u3092\u4f5c\u308b\u65b9\u6cd5\u300d<\/li>\n <li>\u300c\u751f\u6210AI\u3067\u96e3\u89e3\u306a\u6cd5\u4ee4\u3082\u201c3\u5206\u3067\u8aad\u3081\u308b\u201d\u793e\u4f1a\u3092\u76ee\u6307\u3057\u3066\u300d<\/li>\n <\/ul>\n <\/div>\n\n <div class=\"footer\">\n © 2025 \u682a\u5f0f\u4f1a\u793e\u30d3\u30fc\u30fb\u30ca\u30ec\u30c3\u30b8\u30fb\u30c7\u30b6\u30a4\u30f3<br>\n \u672c\u8a18\u4e8b\u30fb\u30b5\u30f3\u30d7\u30eb\u306f\u5b66\u7fd2\u76ee\u7684\u30fb\u500b\u4eba\u5229\u7528\u5411\u3051\u3067\u3059\u3002API\u5229\u7528\u306f\u5404\u30b5\u30fc\u30d3\u30b9\u306e\u898f\u7d04\u3092\u5b88\u3063\u3066\u304f\u3060\u3055\u3044\u3002\n <\/div>\n<\/body>\n<\/html>\n\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u751f\u6210AI\u3067\u6cd5\u4ee4\u6587\u7ae0\u3092\u8981\u7d04\u3057\u3001\u6cd5\u52d9\u306e\u52c9\u5f37\u306b\u4f7f\u3063\u3066\u307f\u305f\uff5c\u5b9f\u8df5\u30b9\u30c6\u30c3\u30d7\u8b1b\u5ea7 \u306f\u3058\u3081\u306b\uff1a\u306a\u305c\u6cd5\u4ee4\u6587\u7ae0\u306e\u8981\u7d04\u304c\u91cd\u8981\u304b\uff1f \u6cd5\u52d9\u3084\u884c\u653f\u3001\u7d4c\u55b6\u306b\u643a\u308f\u308b\u4eba\u306b\u3068\u3063\u3066\u3001\u6cd5\u4ee4\u3084\u898f\u5247\u3092\u6b63\u78ba\u304b\u3064\u52b9\u7387\u7684\u306b\u7406\u89e3\u3059\u308b\u3053\u3068\u306f\u975e\u5e38\u306b\u5927\u5207\u3067\u3059\u3002\u3057\u304b\u3057\u3001\u6cd5\u4ee4\u539f\u6587 […]<\/p>\n","protected":false},"author":1,"featured_media":1301,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"saved_in_kubio":false,"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"vkexunit_cta_each_option":"","footnotes":""},"categories":[5,6,54],"tags":[],"class_list":["post-1296","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","category-programing","category-54"],"aioseo_notices":[],"jetpack_featured_media_url":"https:\/\/beeknowledge.co.jp\/wp-content\/uploads\/2025\/06\/m6mccqm.jpg","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=\/wp\/v2\/posts\/1296","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1296"}],"version-history":[{"count":5,"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=\/wp\/v2\/posts\/1296\/revisions"}],"predecessor-version":[{"id":1302,"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=\/wp\/v2\/posts\/1296\/revisions\/1302"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=\/wp\/v2\/media\/1301"}],"wp:attachment":[{"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1296"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1296"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1296"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}

$\"\"$ <\/div>\n\n\n\n \n \u751f\u6210AI\u3067\u6cd5\u4ee4\u6587\u7ae0\u3092\u8981\u7d04\u3057\u3001\u6cd5\u52d9\u306e\u52c9\u5f37\u306b\u4f7f\u3063\u3066\u307f\u305f\uff5c\u5b9f\u8df5\u30b9\u30c6\u30c3\u30d7\u8b1b\u5ea7<\/title>\n <style>\n body { max-width: 900px; margin: 0 auto; font-family: \"Yu Gothic\", YuGothic, sans-serif; background: #f7f7fa; color: #222; }\n h1, h2, h3 { color: #006699; }\n pre, code { background: #eee; padding: 1em; border-radius: 8px; display: block; overflow-x: auto; }\n .step { margin: 2em 0; }\n .graph { margin: 1em 0 2em 0; }\n .tips { background: #e3f6fd; border-left: 4px solid #0096c7; padding: 1em; margin: 2em 0; }\n .footer { margin-top: 4em; padding: 2em 0; border-top: 1px solid #bbb; text-align: center; color: #888; }\n ul,ol { margin: 1em 2em; }\n <\/style>\n<\/head>\n<body>\n\n <div class=\"step\">\n <h2>\u306f\u3058\u3081\u306b\uff1a\u306a\u305c\u6cd5\u4ee4\u6587\u7ae0\u306e\u8981\u7d04\u304c\u91cd\u8981\u304b\uff1f<\/h2>\n <p>\n \u6cd5\u52d9\u3084\u884c\u653f\u3001\u7d4c\u55b6\u306b\u643a\u308f\u308b\u4eba\u306b\u3068\u3063\u3066\u3001\u6cd5\u4ee4\u3084\u898f\u5247\u3092\u6b63\u78ba\u304b\u3064\u52b9\u7387\u7684\u306b\u7406\u89e3\u3059\u308b\u3053\u3068\u306f\u975e\u5e38\u306b\u5927\u5207\u3067\u3059\u3002\u3057\u304b\u3057\u3001\u6cd5\u4ee4\u539f\u6587\u306f\u9577\u304f\u3001\u5c02\u9580\u7528\u8a9e\u304c\u591a\u304f\u3001\u4e00\u8aad\u3057\u3066\u8981\u70b9\u3092\u628a\u63e1\u3059\u308b\u306e\u306f\u56f0\u96e3\u3067\u3059\u3002<b>\u751f\u6210AI\uff08\u5927\u898f\u6a21\u8a00\u8a9e\u30e2\u30c7\u30eb\uff1aLLM\uff09<\/b>\u306f\u3001\u305d\u306e\u81a8\u5927\u306a\u6587\u7ae0\u304b\u3089\u8981\u70b9\u3092\u62bd\u51fa\u3057\u3001\u308f\u304b\u308a\u3084\u3059\u3044\u65e5\u672c\u8a9e\u306b\u8981\u7d04\u3059\u308b\u80fd\u529b\u3092\u6301\u3061\u307e\u3059\u3002\u672c\u7a3f\u3067\u306f\u3001\u300c\u751f\u6210AI\u3092\u7528\u3044\u305f\u6cd5\u4ee4\u8981\u7d04\u300d\u306e\u5b9f\u8df5\u624b\u9806\u3068\u5fdc\u7528\u4f8b\u3092\u3001\u5b9f\u969b\u306ePython\u30b5\u30f3\u30d7\u30eb\u30b3\u30fc\u30c9\u3084\u30b0\u30e9\u30d5\u4ed8\u304d\u3067\u89e3\u8aac\u3057\u307e\u3059\u3002\n <\/p>\n <\/div>\n\n <div class=\"step\">\n <h2>STEP 1\uff1a\u6cd5\u4ee4\u30c7\u30fc\u30bf\u306e\u5165\u624b\u3068\u6574\u7406<\/h2>\n <p>\n \u307e\u305a\u3001\u5bfe\u8c61\u3068\u3059\u308b\u6cd5\u4ee4\u6587\u7ae0\uff08\u4f8b\uff1a<a href=\"https:\/\/www.bunka.go.jp\/seisaku\/chosakuken\/seidokaisetsu\/seminar\/2024\/pdf\/94141401_01.pdf\" target=\"_blank\">\u8457\u4f5c\u6a29\u6cd5<\/a>\u3084\u500b\u4eba\u60c5\u5831\u4fdd\u8b77\u6cd5\u306a\u3069\uff09\u3092\u30cd\u30c3\u30c8\u304b\u3089\u53ce\u96c6\u3057\u307e\u3059\u3002\u65e5\u672c\u306e\u6cd5\u4ee4\u306f\u300ce-Gov\u6cd5\u4ee4\u691c\u7d22\u300d\u3084\u5404\u7701\u5e81\u306e\u516c\u958bPDF\u304b\u3089\u5165\u624b\u53ef\u80fd\u3067\u3059\u3002<br>\n <b>\u30dd\u30a4\u30f3\u30c8\uff1a<\/b> <br>\n \u30fbPDF\u3084HTML\u304b\u3089\u30d7\u30ec\u30fc\u30f3\u30c6\u30ad\u30b9\u30c8\u306b\u5909\u63db\uff08\u4f8b\uff1aPython\u306e<code>pdfplumber<\/code>\u3084<code>BeautifulSoup<\/code>\u5229\u7528\uff09<br>\n \u30fb\u5206\u91cf\u304c\u591a\u3044\u5834\u5408\u3001\u6761\u6587\u3054\u3068\u3084\u7ae0\u3054\u3068\u306b\u5206\u5272\u3059\u308b\u3068\u51e6\u7406\u3057\u3084\u3059\u3044\n <\/p>\n <pre><code>\nimport pdfplumber\n\nwith pdfplumber.open(\"94141401_01.pdf\") as pdf:\n text = ''\n for page in pdf.pages:\n text += page.extract_text() + '\\n'\n\nprint(text[:10000]) # \u5148\u982d10000\u5b57\u3060\u3051\u8868\u793a\n <\/code><\/pre>\n <\/div>\n\n <div class=\"step\">\n <h2>STEP 2\uff1a\u751f\u6210AI\uff08GPT\u306a\u3069\uff09\u306b\u3088\u308b\u8981\u7d04<\/h2>\n <p>\n \u53ce\u96c6\u3057\u305f\u6cd5\u4ee4\u6587\u3092\u751f\u6210AI\u306b\u5165\u529b\u3057\u3001\u8981\u7d04\u3092\u4f9d\u983c\u3057\u307e\u3059\u3002gemini\u3084OpenAI\u306eAPI\u3001\u30ed\u30fc\u30ab\u30ebLLM\uff08llama, GPT4All\u7b49\uff09\u3082\u6d3b\u7528\u3067\u304d\u307e\u3059\u3002<br>\n <b>\u4f8b\uff1aGemini API\uff08Python\uff09<\/b>\n <\/p>\n <pre><code>\nimport google.generativeai as genai\n\n# API\u30ad\u30fc\u306fGoogle Cloud Console\u304b\u3089\u53d6\u5f97\u3057\u3066\u304f\u3060\u3055\u3044\ngenai.configure(api_key=\"YOUR_GEMINI_API_KEY\")\n\n# Gemini\u30e2\u30c7\u30eb\u306e\u6307\u5b9a\uff082025\u5e746\u6708\u6642\u70b9\u306e\u6700\u65b0\u7248\uff09\nmodel = genai.GenerativeModel('gemini-1.5-pro-latest')\n\ndef summarize_law(text):\n prompt = f\"\"\"\u3042\u306a\u305f\u306f\u6cd5\u5f8b\u306b\u8a73\u3057\u3044\u5c02\u9580\u5bb6\u3067\u3059\u3002\n\u6b21\u306e\u6cd5\u4ee4\u6587\u7ae0\u3092\u3001\u5c02\u9580\u7528\u8a9e\u306f\u308f\u304b\u308a\u3084\u3059\u3044\u8a00\u8449\u306b\u8a00\u3044\u63db\u3048\u3066\u7c21\u6f54\u306b\u8981\u7d04\u3057\u3066\u304f\u3060\u3055\u3044\u3002\n\n{text}\n\"\"\"\n response = model.generate_content(prompt)\n return response.text\n\n# \u30b5\u30f3\u30d7\u30eb\uff1a1000\u5b57\u305a\u3064\u5206\u5272\u3057\u3066\u51e6\u7406\nparts = [text[i:i+1000] for i in range(0, len(text), 1000)]\nsummaries = [summarize_law(part) for part in parts]\n\nfor s in summaries:\n print(s)\n\n <\/code><\/pre>\n <div class=\"tips\">\n <b>Tips:<\/b> \u8981\u7d04\u3092\u7e70\u308a\u8fd4\u3059\u3053\u3068\u3067\u3001\u7ae0\u3054\u3068\u3001\u6761\u6587\u3054\u3068\u3001\u5168\u4f53\u3068\u300c\u591a\u6bb5\u968e\u8981\u7d04\u300d\u3082\u53ef\u80fd\u3067\u3059\u3002\u751f\u6210AI\u306b\u306f\u660e\u78ba\u306a\u6307\u793a\uff08\u300c\u91cd\u8981\u306a\u90e8\u5206\u306e\u307f\u300d\u306a\u3069\uff09\u3092\u4e0e\u3048\u308b\u306e\u304c\u30b3\u30c4\u3067\u3059\u3002\n <\/div>\n <\/div>\n\n <div class=\"step\">\n <h2>STEP 3\uff1a\u8981\u7d04\u5185\u5bb9\u306e\u5206\u6790\u3068\u53ef\u8996\u5316\uff08\u30b0\u30e9\u30d5\uff09<\/h2>\n <p>\n \u751f\u6210AI\u306b\u3088\u308b\u8981\u7d04\u306e\u4e2d\u304b\u3089\u300c\u983b\u51fa\u30ad\u30fc\u30ef\u30fc\u30c9\u300d\u3084\u300c\u5404\u7ae0\u30fb\u6761\u6587\u306e\u91cd\u8981\u5ea6\u300d\u306a\u3069\u3092\u7d71\u8a08\u7684\u306b\u6574\u7406\u3057\u3001\u30b0\u30e9\u30d5\u3067\u53ef\u8996\u5316\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<br>\n \u4f8b\u3048\u3070\u3001\u6cd5\u4ee4\u8981\u7d04\u304b\u3089\u300c\u500b\u4eba\u60c5\u5831\u300d\u300c\u7b2c\u4e09\u8005\u63d0\u4f9b\u300d\u300c\u672c\u4eba\u540c\u610f\u300d\u306a\u3069\u306e\u30ef\u30fc\u30c9\u51fa\u73fe\u56de\u6570\u3092\u68d2\u30b0\u30e9\u30d5\u3067\u8868\u793a\u3057\u307e\u3059\u3002\n <\/p>\n <pre><code>\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom collections import Counter\n\nall_summary = '\\n'.join(summaries)\nkeywords = ['\u500b\u4eba\u60c5\u5831', '\u7b2c\u4e09\u8005\u63d0\u4f9b', '\u672c\u4eba\u540c\u610f', '\u76ee\u7684\u5916\u5229\u7528', '\u524a\u9664', '\u5229\u7528\u76ee\u7684']\n\ncounter = {k: all_summary.count(k) for k in keywords}\ndf = pd.DataFrame(list(counter.items()), columns=['Keyword', 'Count'])\n\nplt.bar(df['Keyword'], df['Count'])\nplt.title('\u8981\u7d04\u4e2d\u306e\u4e3b\u8981\u30ad\u30fc\u30ef\u30fc\u30c9\u51fa\u73fe\u6570')\nplt.xlabel('\u30ad\u30fc\u30ef\u30fc\u30c9')\nplt.ylabel('\u51fa\u73fe\u56de\u6570')\nplt.tight_layout()\nplt.show()\n <\/code><\/pre>\n\n <\/div>\n\n <div class=\"step\">\n <h2>STEP 4\uff1a\u6cd5\u52d9\u306e\u5b66\u7fd2\u3084\u5b9f\u52d9\u3078\u306e\u5fdc\u7528\u30a2\u30a4\u30c7\u30a2<\/h2>\n <ul>\n <li>\u6cd5\u4ee4\u8981\u7d04\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306e\u81ea\u4f5c \u2192 \u65b0\u4eba\u7814\u4fee\u30fb\u8cc7\u683c\u8a66\u9a13\u5bfe\u7b56\u306b\u6d3b\u7528<\/li>\n <li>\u6761\u6587\u306e\u300c\u96e3\u6613\u5ea6\u300d\u300c\u91cd\u8981\u5ea6\u300d\u30e9\u30d9\u30eb\u4ed8\u3051 \u2192 \u52c9\u5f37\u306e\u512a\u5148\u9806\u4f4d\u4ed8\u3051<\/li>\n <li>\u30b1\u30fc\u30b9\u5225QA\u751f\u6210 \u2192 \u5177\u4f53\u7684\u306a\u30b7\u30fc\u30f3\u3067\u306e\u6761\u6587\u9069\u7528\u4f8b\u3082AI\u306b\u81ea\u52d5\u751f\u6210\u3055\u305b\u308b<\/li>\n <li>\u5224\u4f8b\u3084\u5b9f\u52d9\u4e8b\u4f8b\u3092\u542b\u3081\u3066\u591a\u6bb5\u7684\u8981\u7d04 \u2192 \u5b9f\u52d9\u8005\u5411\u3051\u30ca\u30ec\u30c3\u30b8\u30d9\u30fc\u30b9\u69cb\u7bc9<\/li>\n <li>\u97f3\u58f0\u5316\u30fb\u30ea\u30b9\u30cb\u30f3\u30b0\u6559\u6750\u5316 \u2192 AI\u306b\u3088\u308b\u8981\u7d04\u3068\u97f3\u58f0\u5408\u6210\u3067\u6642\u77ed\u5b66\u7fd2<\/li>\n <\/ul>\n <div class=\"tips\">\n <b>\u5b9f\u52d9Tips\uff1a<\/b><br>\n \u6cd5\u4ee4\u306f\u6bce\u5e74\u6539\u6b63\u304c\u5165\u308b\u305f\u3081\u3001AI\u8981\u7d04\uff0b\u4eba\u9593\u306e\u6700\u65b0\u30c1\u30a7\u30c3\u30af\u304c\u5927\u5207\u3067\u3059\u3002<br>\n ChatGPT\u3084Google Gemini\u306f\u65e5\u672c\u8a9e\u306b\u3082\u5f37\u304f\u3001\u6587\u7ae0\u8981\u7d04\u30fb\u5206\u985e\u30fb\u4f8b\u793a\u751f\u6210\u306a\u3069\u591a\u7528\u9014\u306b\u4f7f\u3048\u307e\u3059\u3002\n <\/div>\n <\/div>\n\n <div class=\"step\">\n <h2>STEP 5\uff1a\u793e\u4f1a\u7684\u306a\u610f\u7fa9\u3068\u4eca\u5f8c\u306e\u5c55\u671b\uff08\u8003\u5bdf\uff09<\/h2>\n <p>\n \u6cd5\u4ee4\u6587\u7ae0\u3092AI\u3067\u8981\u7d04\u3059\u308b\u6280\u8853\u306f\u3001\u793e\u4f1a\u306e\u30c7\u30b8\u30bf\u30eb\u30fb\u30ac\u30d0\u30ca\u30f3\u30b9\u306e\u57fa\u76e4\u5f37\u5316\u3001\u6cd5\u6559\u80b2\u306e\u52b9\u7387\u5316\u3001\u884c\u653fDX\u63a8\u9032\u306b\u4e0d\u53ef\u6b20\u3068\u306a\u3063\u3066\u304d\u307e\u3057\u305f\u3002<br>\n \u6cd5\u52d9\u5206\u91ce\u3067\u306f\u3001\u3053\u308c\u307e\u3067\u5f01\u8b77\u58eb\u3084\u884c\u653f\u66f8\u58eb\u304c\u6642\u9593\u3092\u304b\u3051\u3066\u8981\u70b9\u6574\u7406\u3057\u3066\u304d\u305f\u4f5c\u696d\u304c\u3001AI\u306b\u3088\u308a\u5927\u5e45\u306b\u81ea\u52d5\u5316\u3055\u308c\u3064\u3064\u3042\u308a\u307e\u3059\u3002\u305d\u306e\u7d50\u679c\u3001\u3088\u308a\u591a\u304f\u306e\u4eba\u304c\u77ed\u6642\u9593\u3067\u6cd5\u7684\u306a\u77e5\u8b58\u306b\u30a2\u30af\u30bb\u30b9\u3067\u304d\u3001\u696d\u52d9\u306e\u52b9\u7387\u5316\u3084\u8aa4\u89e3\u306e\u524a\u6e1b\u306b\u3064\u306a\u304c\u308a\u307e\u3059\u3002<br>\n \u307e\u305f\u3001\u5b98\u6c11\u3067\u306e\u6cd5\u4ee4\u8981\u7d04\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u6574\u5099\u304c\u9032\u3080\u3053\u3068\u3067\u3001AI\u306b\u3088\u308b\u6cd5\u4ee4\u691c\u7d22\u30fb\u81ea\u52d5\u6587\u66f8\u4f5c\u6210\u30fb\u5224\u4f8b\u81ea\u52d5\u5206\u985e\u3068\u3044\u3063\u305f\u65b0\u305f\u306a\u5fdc\u7528\u3082\u5e83\u304c\u308a\u3064\u3064\u3042\u308a\u307e\u3059\u3002\n <\/p>\n <p>\n <b>\u4eca\u5f8c\u306f\u3001\u300c\u6cd5\u4ee4\u30c7\u30fc\u30bf\uff0b\u751f\u6210AI\u300d\u00d7\u300c\u30d3\u30b8\u30e5\u30a2\u30e9\u30a4\u30ba\u300d\u00d7\u300c\u81ea\u7136\u8a00\u8a9eQA\u5316\u300d<\/b>\u304c\u4e00\u822c\u5316\u3057\u3001\u4f01\u696d\u30fb\u81ea\u6cbb\u4f53\u30fb\u6559\u80b2\u73fe\u5834\u3067\u306e\u5c0e\u5165\u304c\u6025\u901f\u306b\u9032\u3080\u3068\u4e88\u60f3\u3055\u308c\u307e\u3059\u3002\n <\/p>\n <\/div>\n\n <div class=\"step\">\n <h2>\u5fdc\u7528\u30d6\u30ed\u30b0\u30cd\u30bf\u30fb\u8da3\u5473\u3078\u306e\u5e83\u304c\u308a\u4f8b<\/h2>\n <ul>\n <li>\u300cChatGPT\u3067\u516d\u6cd5\u5168\u66f8\u3092\u8981\u7d04\u3057\u3066\u307f\u305f\uff01\u77e5\u3089\u306a\u3044\u6761\u6587\u304c\u8eab\u8fd1\u306b\u306a\u308b\u300d<\/li>\n <li>\u300c\u8cc7\u683c\u8a66\u9a13\u306b\u5f79\u7acb\u3064AI\u6cd5\u4ee4\u8981\u7d04\u30ce\u30fc\u30c8\u306e\u4f5c\u308a\u65b9\u300d<\/li>\n <li>\u300c\u81ea\u4f5cAI\u6cd5\u4ee4\u30dc\u30c3\u30c8\u3067\u201c\u79c1\u306e\u305f\u3081\u306e\u30ea\u30fc\u30ac\u30eb\u76f8\u8ac7\u201d\u300d<\/li>\n <li>\u300cOpenAI\uff0bPython\u3067\u30aa\u30ea\u30b8\u30ca\u30eb\u5224\u4f8b\u8f9e\u66f8\u3092\u4f5c\u308b\u65b9\u6cd5\u300d<\/li>\n <li>\u300c\u751f\u6210AI\u3067\u96e3\u89e3\u306a\u6cd5\u4ee4\u3082\u201c3\u5206\u3067\u8aad\u3081\u308b\u201d\u793e\u4f1a\u3092\u76ee\u6307\u3057\u3066\u300d<\/li>\n <\/ul>\n <\/div>\n\n <div class=\"footer\">\n © 2025 \u682a\u5f0f\u4f1a\u793e\u30d3\u30fc\u30fb\u30ca\u30ec\u30c3\u30b8\u30fb\u30c7\u30b6\u30a4\u30f3<br>\n \u672c\u8a18\u4e8b\u30fb\u30b5\u30f3\u30d7\u30eb\u306f\u5b66\u7fd2\u76ee\u7684\u30fb\u500b\u4eba\u5229\u7528\u5411\u3051\u3067\u3059\u3002API\u5229\u7528\u306f\u5404\u30b5\u30fc\u30d3\u30b9\u306e\u898f\u7d04\u3092\u5b88\u3063\u3066\u304f\u3060\u3055\u3044\u3002\n <\/div>\n<\/body>\n<\/html>\n\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u751f\u6210AI\u3067\u6cd5\u4ee4\u6587\u7ae0\u3092\u8981\u7d04\u3057\u3001\u6cd5\u52d9\u306e\u52c9\u5f37\u306b\u4f7f\u3063\u3066\u307f\u305f\uff5c\u5b9f\u8df5\u30b9\u30c6\u30c3\u30d7\u8b1b\u5ea7 \u306f\u3058\u3081\u306b\uff1a\u306a\u305c\u6cd5\u4ee4\u6587\u7ae0\u306e\u8981\u7d04\u304c\u91cd\u8981\u304b\uff1f \u6cd5\u52d9\u3084\u884c\u653f\u3001\u7d4c\u55b6\u306b\u643a\u308f\u308b\u4eba\u306b\u3068\u3063\u3066\u3001\u6cd5\u4ee4\u3084\u898f\u5247\u3092\u6b63\u78ba\u304b\u3064\u52b9\u7387\u7684\u306b\u7406\u89e3\u3059\u308b\u3053\u3068\u306f\u975e\u5e38\u306b\u5927\u5207\u3067\u3059\u3002\u3057\u304b\u3057\u3001\u6cd5\u4ee4\u539f\u6587 […]<\/p>\n","protected":false},"author":1,"featured_media":1301,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"saved_in_kubio":false,"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"vkexunit_cta_each_option":"","footnotes":""},"categories":[5,6,54],"tags":[],"class_list":["post-1296","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","category-programing","category-54"],"aioseo_notices":[],"jetpack_featured_media_url":"https:\/\/beeknowledge.co.jp\/wp-content\/uploads\/2025\/06\/m6mccqm.jpg","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=\/wp\/v2\/posts\/1296","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1296"}],"version-history":[{"count":5,"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=\/wp\/v2\/posts\/1296\/revisions"}],"predecessor-version":[{"id":1302,"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=\/wp\/v2\/posts\/1296\/revisions\/1302"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=\/wp\/v2\/media\/1301"}],"wp:attachment":[{"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1296"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1296"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/beeknowledge.co.jp\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1296"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}