This tool extracts main text from xml Wikipedia dump files (at http://dumps.wikimedia.org/backup-index.html, ideally the "pages-articles" file), producing a text corpus, which is useful for training unsupervised part-of-speech taggers, n-gram language models, etc.
It was modified by a number of people, including by BenStobaugh during Google Code-In 2013, and can be cloned from GitHub at https://github.com/apertium/WikiExtractor.
This version is much simpler than the old version. This version auto-removes any formatting and only outputs the text to one file. To use it, simply use the following command in your terminal, where dump.xml is the Wikipedia dump
$ python3 WikiExtractor.py --infn dump.xml.bz2
(Note: If you are on a Mac, make sure that -- is really two hyphens and not an em-dash like this: —).
This will run through all of the articles, get all of the text and put it in wiki.txt. This version also supports compression (BZip2 and Gzip), so you can use
dump.xml.gz instead of
dump.xml. You can also compress (Bzip2) the output file by adding
--compress to the command.
You can also run
python3 WikiExtractor.py --help to get more details.
Here's a simple step-by-step guide to the above.
- Get the
WikiExtractor.pyscript from https://github.com/apertium/WikiExtractor:
- Download the Wikipedia dump for the language in question from http://dumps.wikimedia.org/backup-index.html. The below uses a hypothetical file name for a language with the xyz code:
- Run the script on the Wikipedia dump file:
$ python3 WikiExtractor.py --infn xyzwiki-20210620-pages-articles.xml.bz2 --compress
This will output a file called
wiki.txt.bz2. You will probably want to rename it to something like