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Japanese word segmentation/POS tagging tool based on neural networks

Project description

![Alt text](/nagisa/data/nagisa_image.jpg 'An image of title')

# nagisa

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[Japanese (slideshare)](https://www.slideshare.net/100003383562829/rnn-90731229)

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 features [[池田+]](http://www.anlp.jp/proceedings/annual_meeting/2017/pdf_dir/B6-2.pdf).
- The POS-tagging model uses tag dictionary information [[Inoue+]](http://www.aclweb.org/anthology/K17-1042).

<img src='/nagisa/data/models.jpg' width='640px'>

Requirements
========
[DyNet](https://github.com/clab/dynet) (Neural Network Toolkit) is required.
Nagisa is compatible with: Python 2.7-3.6.

Installation
========

Using pip
```bash
pip install nagisa
```

From github
```bash
git clone https://github.com/taishi-i/nagisa
cd nagisa
python setup.py install
# If you got a permission denied error, please run the following line.
# sudo python setup.py install
```

Usage
====

```python
import nagisa
tagger = nagisa.Tagger()

# Sample of word segmentation and POS-tagging for Japanese
text = 'Pythonで簡単に使えるツールです'
words = tagger.tagging(text)
print(words) # 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
print(words.words) # ['Python', 'で', '簡単', 'に', '使える', 'ツール', 'です']
# Get a list of POS-tags
print(words.postags) # ['名詞', '助詞', '形状詞', '助動詞', '動詞', '名詞', '助動詞']
```

Features
====

Output words can be controlled by POS-tags.
```python
# Extarcting all nouns from a text
words = tagger.extract(text, extract_postags=['名詞'])
print(words) # Python/名詞 ツール/名詞

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

# A list of available POS-tags
print(tagger.postags) # ['補助記号', '名詞', ... , 'URL']

```

A word can be recognized as a single word forcibly.
```python
text = 'ニューラルネットワークを使ってます。'
print(tagger.tagging(text)) # 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'])
print(tagger_nn.tagging(text)) # 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 URLs and emoticons from an input text.
```python
text = '(人•ᴗ•♡)こんばんは♪'
words = tagger.tagging(text)
print(words) # (人•ᴗ•♡)/補助記号 こんばんは/感動詞 ♪/補助記号

url = 'https://github.com/taishi-i/nagisaでコードを公開中(๑¯ω¯๑)'
words = tagger.tagging(url)
print(words) # https://github.com/taishi-i/nagisa/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

words = tagger.filter(url, filter_postags=['URL', '補助記号', '助詞'])
print(words) # コード/名詞 公開/名詞 中/接尾辞
```

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