pybo: A Python repository from mikkokotila

Overview

pybo is a word tokenizer for the Tibetan language entirely written in Python. pybo takes in chuncks of text, and returns lists of words. It provides an easy-to-use, high-performance tokenization pipeline that can be adapted either as a stand-alone solution or compliment.

Getting Started

pip install pybo

Or if you for some reason want to install from the latest Master branch:

pip install git+https://github.com/Esukhia/pybo.git

Use

To initiate the tokenizer together with part-of-speech capability:

# initialize the tokenizer
tok = bo.BoTokenizer('POS')

# read in some Tibetan text
input_str = '༄༅། །རྒྱ་གར་སྐད་དུ། བོ་དྷི་སཏྭ་ཙརྻ་ཨ་བ་ཏ་ར། བོད་སྐད་དུ། བྱང་ཆུབ་སེམས་དཔའི་སྤྱོད་པ་ལ་འཇུག་པ། །སངས་རྒྱས་དང་བྱང་ཆུབ་སེམས་དཔའ་ཐམས་ཅད་ལ་ཕྱག་འཚལ་ལོ། །བདེ་གཤེགས་ཆོས་ཀྱི་སྐུ་མངའ་སྲས་བཅས་དང༌། །ཕྱག་འོས་ཀུན་ལའང་གུས་པར་ཕྱག་འཚལ་ཏེ། །བདེ་གཤེགས་སྲས་ཀྱི་སྡོམ་ལ་འཇུག་པ་ནི། །ལུང་བཞིན་མདོར་བསྡུས་ནས་ནི་བརྗོད་པར་བྱ། །'

# run the tokenizer
tokens = tok.tokenize(input_str)

Now in 'tokens' you have an iterable where each token consist of several meta-data:

# access the first token in the iterable
tokens[0]

This will yield:

content: "༄༅། "
char_types: |punct|punct|punct|space|
type: punct
start: 0
len: 4
syls: None
tag: punct
pos: punct
skr: "False"
freq: 0

notes:

start is the starting index of the current token in the input string.
syls is a list of cleaned syllables, each syllable being represented as a list of indices. Each index leads to a constituting character within the input string.

In case you want to access all words in a list:

# iterate through the tokens object to get all the words in a list
[t.content for t in tokens]

Or just get all the nouns that were used in the text

# extract nouns from the tokens
[t.content for t in tokens if t.tag == 'NOUNᛃᛃᛃ']

These examples highlight the basic principle of accessing attributes within each token object.

Acknowledgement

pybo is an open source library for Tibetan NLP.

We are always open to cooperation in introducing new features, tool integrations and testing solutions.

Many thanks to companies and organizations who supported the development of pybo, especially:

Khyentse Foundation for contributing USD22,000 to kickstart the project
The Barom/Esukhia canon project for sponsoring training data curation
BDRC for contributing 2 staff for 6 months for data curation

Maintainance

Build the source dist:

rm -rf dist/
python3 setup.py clean sdist

and upload on twine (versio >= 1.11.0) with:

twine upload dist/*

License

author: Drupchen

contributors:

mikkokotila/pybo