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A Japanese tokenizer based on recurrent neural networks

Project description

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|Build Status| |Documentation Status| |PyPI|

| Nagisa is a python module for Japanese word segmentation/POS-tagging.
| It is designed to be a simple and easy-to-use tool.

This tool has the following features. - Based on recurrent neural
networks. - The word segmentation model uses character- and word-level
`[池田+] <>`__.
- The POS-tagging model uses tag dictionary information
`[Inoue+] <>`__.

For more details refer to the following links. - The slide in Japanese
is available
`here <>`__.
- The documentation is available
`here <>`__.


| Python 2.7.x or 3.5+ is required.
| This tool uses `DyNet <>`__ (the Dynamic
Neural Network Toolkit) to calcucate neural networks.
| You can install nagisa by using the following command.

.. code:: bash

pip install nagisa


Basic usage.

.. code:: python

import nagisa

# Sample of word segmentation and POS-tagging for Japanese
text = 'Pythonで簡単に使えるツールです'
words = nagisa.tagging(text)
#=> Python/名詞 で/助詞 簡単/形状詞 に/助動詞 使える/動詞 ツール/名詞 です/助動詞

# Get a list of words
#=> ['Python', 'で', '簡単', 'に', '使える', 'ツール', 'です']

# Get a list of POS-tags
#=> ['名詞', '助詞', '形状詞', '助動詞', '動詞', '名詞', '助動詞']

# The nagisa.wakati method is faster than the nagisa.tagging method.
words = nagisa.wakati(text)
#=> ['Python', 'で', '簡単', 'に', '使える', 'ツール', 'です']

Post processing functions.

.. code:: python

# Extarcting all nouns from a text
words = nagisa.extract(text, extract_postags=['名詞'])
#=> Python/名詞 ツール/名詞

# Filtering specific POS-tags from a text
words = nagisa.filter(text, filter_postags=['助詞', '助動詞'])
#=> Python/名詞 簡単/形状詞 使える/動詞 ツール/名詞

# A list of available POS-tags
#=> ['補助記号', '名詞', ... , 'URL']

# A word can be recognized as a single word forcibly.
text = 'ニューラルネットワークを使ってます。'
#=> ニューラル/名詞 ネットワーク/名詞 を/助詞 使っ/動詞 て/助動詞 ます/助動詞 。/補助記号

# If a word is included in the single_word_list, it is recognized as a single word.
tagger_nn = nagisa.Tagger(single_word_list=['ニューラルネットワーク'])
#=> ニューラルネットワーク/名詞 を/助詞 使っ/動詞 て/助動詞 ます/助動詞 。/補助記号

# Nagisa is good at capturing the URLs and kaomoji from an input text.
url = 'でコードを公開中(๑¯ω¯๑)'
words = nagisa.tagging(url)
#=> で/助詞 コード/名詞 を/助詞 公開/名詞 中/接尾辞 (๑ ̄ω ̄๑)/補助記号

.. |Build Status| image::
.. |Documentation Status| image::
.. |PyPI| image::

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