Difference between revisions of "Wikipedia Extractor"
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A single script to extract wikipedia dumps to text format (able to take compressed input and write compressed output) based on the documentation below was put together by BenStobaugh during GCI 2013. It is available in SVN at [https://svn.code.sf.net/p/apertium/svn/trunk/apertium-tools/WikiExtractor.py https://svn.code.sf.net/p/apertium/svn/trunk/apertium-tools/WikiExtractor.py] |
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== Goal == |
== Goal == |
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Revision as of 17:19, 9 December 2013
A single script to extract wikipedia dumps to text format (able to take compressed input and write compressed output) based on the documentation below was put together by BenStobaugh during GCI 2013. It is available in SVN at https://svn.code.sf.net/p/apertium/svn/trunk/apertium-tools/WikiExtractor.py
Goal
This tool extracts main text from Wikipedia, producing a text corpus, which is useful for training unsupervised part-of-speech taggers, n-gram language models, etc.
Tool
http://code.google.com/p/natural-language-qa/source/browse/MakeCorpus/WikiExtractor.py
License GPL-V3.
Applicable
Work well : Wikipedia, Wikivoyage, Wikibooks
With problem: Wiktionary (Mistakenly, not all articles fully included, and foreign words' explanations included.)
(Thanks to the feedback by Per Tunedal!)
Usage
1. Get the script
http://code.google.com/p/natural-language-qa/source/browse/MakeCorpus/WikiExtractor.py
2. Download the Wikipedia dump file
http://dumps.wikimedia.org/backup-index.html
Take Chinese as an example, download the file zhwiki-20130625-pages-articles.xml.bz2 on this page http://dumps.wikimedia.org/zhwiki/20130625/. Alternatively, we can download the latest version on this page, http://dumps.wikimedia.org/zhwiki/lastest/
3. Use the script
mkdir output bzcat zhwiki-20130625-pages-articles.xml.bz2 | ./WikiExtractor -o output cat output/*/* > zhwiki.text
Optionally, we can use
"-c" for compression for saving disk space, and
"-b" for setting specified bytes per output file.
More information please type "./WikiExtractor --help".
Ok, let's have a cup of tea and come back an hour later. The output should be output/AA/wikiXX, where wikiXX are the extracted texts.
4. clean up "<>" tags
We are only one step away from the final text corpus, because there are still links in wikiXX files. Let's use the following tiny script to filter out "<>" tags and special "__XXX__" marks.
#! /usr/bin/python # -*- coding:utf-8 -*- import sys import re re1 = re.compile(ur"<.*?>") # ref tags re2 = re.compile(ur"__[A-Z]+__") # special marks e.g. __TOC__ __NOTOC__ line = sys.stdin.readline() while line != "": line = re1.sub("", re2.sub("", line)) print line, line = sys.stdin.readline()
Save the above lines in a file filter.py, and:
python filter.py < zhwiki.text > zhwiki.filter.text