Python Word Segmentation

WordSegment is an Apache2 licensed module for English word segmentation, written in pure-Python, and based on a trillion-word corpus.

Based on code from the chapter "Natural Language Corpus Data" by Peter Norvig from the book "Beautiful Data" (Segaran and Hammerbacher, 2009).

Data files are derived from the Google Web Trillion Word Corpus, as described by Thorsten Brants and Alex Franz, and distributed by the Linguistic Data Consortium. This module contains only a subset of that data. The unigram data includes only the most common 333,000 words. Similarly, bigram data includes only the most common 250,000 phrases. Every word and phrase is lowercased with punctuation removed.

Features

Pure-Python
Fully documented
100% Test Coverage
Includes unigram and bigram data
Command line interface for batch processing
Easy to hack (e.g. different scoring, new data, different language)
Developed on Python 2.7
Tested on CPython 2.6, 2.7, 3.2, 3.3, 3.4 and PyPy 2.5+, PyPy3 2.4+

Quickstart

Installing WordSegment is simple with pip:

$ pip install wordsegment

You can access documentation in the interpreter with Python's built-in help function:

>>> import wordsegment
>>> help(wordsegment)

Tutorial

In your own Python programs, you'll mostly want to use segment to divide a phrase into a list of its parts:

>>> from wordsegment import segment
>>> segment('thisisatest')
['this', 'is', 'a', 'test']

WordSegment also provides a command-line interface for batch processing. This interface accepts two arguments: in-file and out-file. Lines from in-file are iteratively segmented, joined by a space, and written to out-file. Input and output default to stdin and stdout respectively.

$ echo thisisatest | python -m wordsegment
this is a test

The maximum segmented word length is 24 characters. Neither the unigram nor bigram data contain words exceeding that length. The corpus also excludes punctuation and all letters have been lowercased. Before segmenting text, clean is called to transform the input to a canonical form:

>>> from wordsegment import clean
>>> clean('She said, "Python rocks!"')
'shesaidpythonrocks'
>>> segment('She said, "Python rocks!"')
['she', 'said', 'python', 'rocks']

Sometimes its interesting to explore the unigram and bigram counts themselves. These are stored in Python dictionaries mapping word to count.

>>> import wordsegment as ws
>>> ws.load()
>>> ws.UNIGRAMS['the']
23135851162.0
>>> ws.UNIGRAMS['gray']
21424658.0
>>> ws.UNIGRAMS['grey']
18276942.0

Above we see that the spelling gray is more common than the spelling grey.

Bigrams are joined by a space:

>>> import heapq
>>> from pprint import pprint
>>> from operator import itemgetter
>>> pprint(heapq.nlargest(10, ws.BIGRAMS.items(), itemgetter(1)))
[('of the', 2766332391.0),
 ('in the', 1628795324.0),
 ('to the', 1139248999.0),
 ('on the', 800328815.0),
 ('for the', 692874802.0),
 ('and the', 629726893.0),
 ('to be', 505148997.0),
 ('is a', 476718990.0),
 ('with the', 461331348.0),
 ('from the', 428303219.0)]

Some bigrams begin with <s>. This is to indicate the start of a bigram:

>>> ws.BIGRAMS['<s> where']
15419048.0
>>> ws.BIGRAMS['<s> what']
11779290.0

The unigrams and bigrams data is stored in the wordsegment_data directory in the unigrams.txt and bigrams.txt files respectively.

Reference and Indices

WordSegment License

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0