underthesea 1.1.1

Vietnamese NLP Toolkit

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Under The Sea - Vietnamese NLP Toolkit
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**underthesea** is a suite of open source Python modules, data sets and tutorials supporting research and development in Vietnamese Natural Language Processing.

* Free software: GNU General Public License v3
* Documentation: `https://underthesea.readthedocs.io <https://magizbox-underthesea.readthedocs-hosted.com/en/latest/>`_


Installation
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To install underthesea, simply:

.. code-block:: bash

$ pip install underthesea
✨🍰✨

Satisfaction, guaranteed.

Usage
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* `1. Corpus <#1-corpus>`_
* `2. Word Segmentation <#2-word-segmentation>`_
* `3. POS Tagging <#3-pos-tagging>`_
* `4. Chunking <#4-chunking>`_

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1. Corpus
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.. image:: https://img.shields.io/badge/documents-18k-red.svg
:target: #

.. image:: https://img.shields.io/badge/words-74k-red.svg
:target: #

Collection of Vietnamese corpus

* `Vietnamese Dictionary (74k words) <https://github.com/magizbox/underthesea/tree/master/underthesea/corpus/data>`_

* `Vietnamese News Corpus (10k documents) <https://github.com/magizbox/corpus.vinews>`_
* `Vietnamese Wikipedia Corpus (8k documents) <https://github.com/magizbox/corpus.viwiki>`_

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2. Word Segmentation
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.. image:: https://img.shields.io/badge/F1-97%25-red.svg
:target: https://github.com/magizbox/underthesea.word_sent

.. image:: https://img.shields.io/badge/%E2%98%85-can%20beat%20it%3F-blue.svg
:target: https://github.com/magizbox/underthesea.word_sent

Vietnamese Word Segmentation using Conditional Random Fields

* `Word Segmentation API <https://magizbox-underthesea.readthedocs-hosted.com/en/latest/api.html#word-sent-package>`_
* `Word Segmentation Experiences <https://github.com/magizbox/underthesea.word_sent>`_

.. code-block:: python

>>> # -*- coding: utf-8 -*-
>>> from underthesea import word_sent
>>> sentence = u"Chúng ta thường nói đến Rau sạch, Rau an toàn để phân biệt với các rau bình thường bán ngoài chợ."

>>> word_sent(sentence)
[u"Chúng ta", u"thường", u"nói", u"đến", u"Rau sạch", u",", u"Rau", u"an toàn", u"để", u"phân biệt", u"với",
u"các", u"rau", u"bình thường", u"bán", u"ngoài", u"chợ", u"."]

>>> word_sent(sentence, format="text")
u'Chúng_ta thường nói đến Rau_sạch , Rau an_toàn để phân_biệt với các rau bình_thường bán ngoài chợ .'

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3. POS Tagging
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.. image:: https://img.shields.io/badge/accuracy-92.3%25-red.svg
:target: https://github.com/magizbox/underthesea.pos_tag

.. image:: https://img.shields.io/badge/%E2%98%85-can%20beat%20it%3F-blue.svg
:target: https://github.com/magizbox/underthesea.pos_tag

Vietnamese Part of Speech Tagging using Conditional Random Fields

* `POS Tagging API <https://magizbox-underthesea.readthedocs-hosted.com/en/latest/api.html#pos-tag-package>`_
* `Pos Tagging Experiences <https://github.com/magizbox/underthesea.pos_tag>`_

.. code-block:: python

>>> # -*- coding: utf-8 -*-
>>> from underthesea import pos_tag
>>> text = u"Chợ thịt chó nổi tiếng ở TP Hồ Chí Minh bị truy quét"
>>> pos_tag(text)
[(u'Chợ', 'N'),
(u'thịt', 'N'),
(u'chó', 'N'),
(u'nổi tiếng', 'A'),
(u'ở', 'E'),
(u'TP HCM', 'Np'),
(u'bị', 'V'),
(u'truy quét', 'V')]

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4. Chunking
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.. image:: https://img.shields.io/badge/F1-85.1%25-red.svg
:target: https://github.com/magizbox/underthesea.chunking

.. image:: https://img.shields.io/badge/%E2%98%85-can%20beat%20it%3F-blue.svg
:target: https://github.com/magizbox/underthesea.chunking

Vietnamese Chunking using Conditional Random Fields

* `Chunking API <https://magizbox-underthesea.readthedocs-hosted.com/en/latest/api.html#chunking-package>`_
* `Chunking Experiences <https://github.com/magizbox/underthesea.chunking>`_

.. code-block:: python

>>> # -*- coding: utf-8 -*-
>>> from underthesea import chunk
>>> text = u"Bác sĩ bây giờ có thể thản nhiên báo tin bệnh nhân bị ung thư?"
>>> chunk(text)
[(u'Bác sĩ', 'N', 'B-NP'),
(u'bây giờ', 'P', 'I-NP'),
(u'có thể', 'R', 'B-VP'),
(u'thản nhiên', 'V', 'I-VP'),
(u'báo tin', 'N', 'B-NP'),
(u'bệnh nhân', 'N', 'I-NP'),
(u'bị', 'V', 'B-VP'),
(u'ung thư', 'N', 'I-VP'),
(u'?', 'CH', 'O')]

Up Coming Features
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* Word Representation (`Word Representation Experiences <https://github.com/magizbox/underthesea.word_representation>`_)
* Dependency Parsing (Experiences)
* Named Entity Recognition
* Sentiment Analysis

Contributing
----------------------------------------

Do you want to contribute with underthesea development? Great! Please read more details at `CONTRIBUTING.rst. <https://github.com/magizbox/underthesea/blob/master/CONTRIBUTING.rst>`_


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History
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1.1.0(2017-05-30)
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* Add chunking feature
* Add pos_tag feature
* Add word_sent feature, fix performance
* Add Corpus class
* Add Transformer classes
* Integrated with dictionary of Ho Ngoc Duc
* Add travis-CI, auto build with PyPI

1.0.0 (2017-03-01)
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* First release on PyPI.
* First release on Readthedocs