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        "author": "Hai Liang Wang",
        "author_email": "hailiang.hl.wang@gmail.com",
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            "Intended Audience :: Developers",
            "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
            "Natural Language :: Chinese (Simplified)",
            "Natural Language :: Chinese (Traditional)",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Text Processing",
            "Topic :: Text Processing :: Indexing",
            "Topic :: Text Processing :: Linguistic"
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        "description": "\ninsuranceqa-corpus-zh\n=====================\n\n\u4fdd\u9669\u884c\u4e1a\u8bed\u6599\u5e93\n\nWelcome\n-------\n\n\u8be5\u8bed\u6599\u5e93\u5305\u542b\u4ece\u7f51\u7ad9\\ `Insurance\nLibrary <http://www.insurancelibrary.com/>`__ \u6536\u96c6\u7684\u95ee\u9898\u548c\u7b54\u6848\u3002\n\n\u636e\u6211\u4eec\u6240\u77e5\uff0c\u8fd9\u662f\u4fdd\u9669\u9886\u57df\u9996\u4e2a\u5f00\u653e\u7684QA\u8bed\u6599\u5e93\uff1a\n\n-  \u8be5\u8bed\u6599\u5e93\u7684\u5185\u5bb9\u7531\u73b0\u5b9e\u4e16\u754c\u7684\u7528\u6237\u63d0\u51fa\uff0c\u9ad8\u8d28\u91cf\u7684\u7b54\u6848\u7531\u5177\u6709\u6df1\u5ea6\u9886\u57df\u77e5\u8bc6\u7684\u4e13\u4e1a\u4eba\u58eb\u63d0\u4f9b\u3002\n   \u6240\u4ee5\u8fd9\u662f\u4e00\u4e2a\u5177\u6709\u771f\u6b63\u4ef7\u503c\u7684\u8bed\u6599\uff0c\u800c\u4e0d\u662f\u73a9\u5177\u3002\n\n-  \u5728\u4e0a\u8ff0\u8bba\u6587\u4e2d\uff0c\u8bed\u6599\u5e93\u7528\u4e8e\u7b54\u590d\u9009\u62e9\u4efb\u52a1\u3002\n   \u53e6\u4e00\u65b9\u9762\uff0c\u8fd9\u79cd\u8bed\u6599\u5e93\u7684\u5176\u4ed6\u7528\u6cd5\u4e5f\u662f\u53ef\u80fd\u7684\u3002\n   \u4f8b\u5982\uff0c\u901a\u8fc7\u9605\u8bfb\u7406\u89e3\u7b54\u6848\uff0c\u89c2\u5bdf\u5b66\u4e60\u7b49\u81ea\u4e3b\u5b66\u4e60\uff0c\u4f7f\u7cfb\u7edf\u80fd\u591f\u6700\u7ec8\u62ff\u51fa\u81ea\u5df1\u7684\u770b\u4e0d\u89c1\u7684\u95ee\u9898\u7684\u7b54\u6848\u3002\n\n\u6b22\u8fce\u4efb\u4f55\u8fdb\u4e00\u6b65\u589e\u52a0\u6b64\u6570\u636e\u96c6\u7684\u60f3\u6cd5\u3002\n\n\u9605\u8bfb `\u8be6\u7ec6\u6587\u6863 <https://github.com/Samurais/insuranceqa-corpus-zh>`__\n\n\u58f0\u660e\n----\n\n\u58f0\u660e1 :\n`insuranceqa-corpus-zh <https://github.com/Samurais/insuranceqa-corpus-zh>`__\n\n\u672c\u6570\u636e\u96c6\u4f7f\u7528\u7ffb\u8bd1\n`insuranceQA <https://github.com/shuzi/insuranceQA>`__\\ \u800c\u751f\u6210\uff0c\u4ee3\u7801\u53d1\u5e03\u8bc1\u4e66\nGPL\n3.0\u3002\u6570\u636e\u4ec5\u9650\u4e8e\u7814\u7a76\u7528\u9014\uff0c\u5982\u679c\u5728\u53d1\u5e03\u7684\u4efb\u4f55\u5a92\u4f53\u3001\u671f\u520a\u3001\u6742\u5fd7\u6216\u535a\u5ba2\u7b49\u5185\u5bb9\u65f6\uff0c\u5fc5\u987b\u6ce8\u660e\u5f15\u7528\u548c\u5730\u5740\u3002\n\n::\n\n    InsuranceQA Corpus, Hai Liang Wang, https://github.com/Samurais/insuranceqa-corpus-zh, 07 27, 2017\n\n\u4efb\u4f55\u57fa\u4e8e\\ `insuranceqa-corpus <https://github.com/Samurais/insuranceqa-corpus-zh>`__\\ \u884d\u751f\u7684\u6570\u636e\u4e5f\u9700\u8981\u5f00\u653e\u5e76\u9700\u8981\u58f0\u660e\u548c\u201c\u58f0\u660e1\u201d\u548c\u201c\u58f0\u660e2\u201d\u4e00\u81f4\u7684\u5185\u5bb9\u3002\n\n\u58f0\u660e2 : `insuranceQA <https://github.com/shuzi/insuranceQA>`__\n\n\u6b64\u6570\u636e\u96c6\u4ec5\u4f5c\u4e3a\u7814\u7a76\u76ee\u7684\u63d0\u4f9b\u3002\u5982\u679c\u60a8\u4f7f\u7528\u8fd9\u4e9b\u6570\u636e\u53d1\u8868\u4efb\u4f55\u5185\u5bb9\uff0c\u8bf7\u5f15\u7528\u6211\u4eec\u7684\u8bba\u6587\uff1a\\ `Applying\nDeep Learning to Answer Selection: A Study and An Open\nTask <https://arxiv.org/abs/1508.01585>`__\\ \u3002Minwei Feng, Bing Xiang,\nMichael R. Glass, Lidan Wang, Bowen Zhou @ 2015\n",
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