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    "info": {
        "author": "Konstantin Lopukhin, Grigory Nosyrev",
        "author_email": "kostia.lopuhin@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5"
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        "description": "Sense frequencies and WSD\n=========================\n\nThis repository contains scripts and expriments related to the\n`Sense frequencies project <http://sensefreq.ruslang.ru>`_, and an ``rlwsd``\npython package for WSD (word sense disambiguation) for Russian language.\n\n\nrlwsd package\n-------------\n\nThis package can perform WSD for Russian nouns described in the\nof Active Dictionary of Russian (currently, only the first volume is published\nwith letters \"\u0410\" - \"\u0413\").\n\n\nInstallation\n~~~~~~~~~~~~\n\nThe package currently works only on CPython 3.4+. Install with pip::\n\n    pip3 install rlwsd\n\nThe package requires models that are not hosted on PyPI and most be\ndownloaded separately (about 2.3 Gb total)::\n\n    python3 -m rlwsd.download\n\nModels are re-downloaded even if they are already present.\nIn case of problems (download does not finish, etc.) you can download models\nmanually from ``rlwsd.download.MODELS_URL``\nand extract them into the ``models`` folder inside ``rlwsd`` (package) folder.\n\n\nUsage\n~~~~~\n\nMost functionality is provided by the model class. Model for each word\nmust be loaded separately::\n\n    >>> import rlwsd\n    >>> model = rlwsd.SphericalModel.load('\u0430\u043b\u044c\u0431\u043e\u043c')\n    >>> model.senses\n    {'1': {'meaning': '\u0412\u0435\u0449\u044c \u0432 \u0432\u0438\u0434\u0435 \u0431\u043e\u043b\u044c\u0448\u043e\u0439 \u0442\u0435\u0442\u0440\u0430\u0434\u0438 ...',\n           'name': '\u0430\u043b\u044c\u0431\u043e\u043c 1'},\n     '2': {'meaning': '\u041a\u043d\u0438\u0433\u0430 \u0442\u0435\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0438 \u0441\u0432\u044f\u0437\u0430\u043d\u043d\u044b\u0445 \u0438\u0437\u043e\u0431\u0440\u0430\u0437\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0445 \u043c\u0430\u0442\u0435\u0440\u0438\u0430\u043b\u043e\u0432 ...',\n           'name': '\u0430\u043b\u044c\u0431\u043e\u043c 2.1'},\n     '3': {'meaning': '\u0421\u043e\u0431\u0440\u0430\u043d\u0438\u0435 \u043c\u0443\u0437\u044b\u043a\u0430\u043b\u044c\u043d\u044b\u0445 \u043f\u0440\u043e\u0438\u0437\u0432\u0435\u0434\u0435\u043d\u0438\u0439 ...',\n           'name': '\u0430\u043b\u044c\u0431\u043e\u043c 2.2'}}\n    >>> model.disambiguate('\u043e\u043d\u0430 \u0437\u0430\u0434\u0443\u043c\u0447\u0438\u0432\u043e \u043b\u0438\u0441\u0442\u0430\u043b\u0430', '\u0430\u043b\u044c\u0431\u043e\u043c', '\u0441 \u0444\u043e\u0442\u043e\u0433\u0440\u0430\u0444\u0438\u044f\u043c\u0438')\n    '2'\n\nYou can also get a list of all words with models::\n\n    >>> import rlwsd\n    >>> rlwsd.list_words()\n    ['\u0430\u0431\u0440\u0438\u043a\u043e\u0441',\n     '\u0430\u0431\u0441\u0443\u0440\u0434',\n     '\u0430\u0432\u0430\u043d\u0433\u0430\u0440\u0434',\n     ...\n     '\u0433\u0443\u0441\u044c',\n     '\u0433\u0443\u0449\u0430']\n\n\nA large word2vec model is used internally. By default it is loaded once,\none the first call to ``.disambiguate`` method, which takes noticeable time.\nThere is an option to load word2vec\nmodel in a separate process by running ``w2v-server`` command, which starts\na server, and exporting ``W2VSRV`` environment variable with any non-empty value::\n\n    # in the first terminal window\n    $ w2v-server\n    running...\n    # in the second terminal window\n    $ export W2VSRV=yes\n    $ python\n\nIn this way you can leave the ``w2v-server`` running and save time on word2vec\nmodel reloads.\n\n\nLicense\n~~~~~~~\n\nLicense is MIT",
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