Difference between revisions of "Wikipedia dumps"
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Wikipedia dumps are useful for quickly getting a corpus. They are also the best corpora for making your language pair are useful for Wikipedia's Content Translation tool :-) |
Wikipedia dumps are useful for quickly getting a corpus. They are also the best corpora for making your language pair are useful for Wikipedia's [[Content Translation]] tool :-) |
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You download them from |
You download them from |
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* http://dumps.wikimedia.org/backup-index.html |
* http://dumps.wikimedia.org/backup-index.html |
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==Tools to turn dumps into plaintext== |
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There are several tools for turning dumps into useful plaintext, e.g. |
There are several tools for turning dumps into useful plaintext, e.g. |
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* [[Wikipedia Extractor]] – a python script that tries to remove all formatting |
* [[Wikipedia Extractor]] – a python script that tries to remove all formatting |
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* [https://github.com/attardi/wikiextractor wikiextractor] – another python script that removes all formatting (with different options), putting XML marks just to know when begins and ends everty single article |
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* [https://gist.github.com/unhammer/3372222878580d1e4c6f mwdump-to-pandoc] – shell wrapper around [http://pandoc.org/ pandoc] (see the usage.sh below the script for how to use) |
* [https://gist.github.com/unhammer/3372222878580d1e4c6f mwdump-to-pandoc] – shell wrapper around [http://pandoc.org/ pandoc] (see the usage.sh below the script for how to use) |
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* [[Calculating_coverage#More_involved_scripts]] – an ugly shell script that does the job |
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* [http://wp2txt.rubyforge.org/ wp2txt] – some ruby thing (does this work?) |
* [http://wp2txt.rubyforge.org/ wp2txt] – some ruby thing (does this work?) |
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==Content Translation dumps== |
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There are also dumps of the articles translated with the Content Translation tool, which uses Apertium (and other MT engines) under the hood: |
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* https://www.mediawiki.org/wiki/Content_translation/Published_translations |
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To turn a tmx into a <code>SOURCE\tMT\tGOLD</code> tab-separated text file, install xmlstarlet (<code>sudo apt install xmlstarlet</code>) and do: |
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<pre> |
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$ zcat ~/Nedlastingar/cx-corpora.nb2nn.text.tmx.gz \ |
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| xmlstarlet sel -t -m '//tu[tuv/prop/text()="mt"]' \ |
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-c 'tuv[./prop/text()="source"]/seg/text()' -o $'\t' \ |
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-c 'tuv[./prop/text()="mt"]/seg/text()' -o $'\t' \ |
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-c 'tuv[./prop/text()="user"]/seg/text()' -n \ |
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> nb2nn.tsv |
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</pre> |
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Now view the word diff between MT and GOLD with: |
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<pre> |
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$ diff -U0 <(cut -f2 nb2nn.tsv) <(cut -f3 nb2nn.tsv) | dwdiff --diff-input -c | less |
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</pre> |
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[[Image:Dwdiff-content-translation.png|600px]] |
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and find the original if you need it in <code>cut -f1 nb2nn.tsv</code>. |
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For some languages, you have to get the _2CODE files or _2_ files, e.g. sv2da is in https://dumps.wikimedia.org/other/contenttranslation/20180810/cx-corpora._2da.text.tmx.gz and da2sv is in https://dumps.wikimedia.org/other/contenttranslation/20180810/cx-corpora._2_.text.tmx.gz – so let's filter it to the languages we want: |
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<pre> |
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$ zcat ~/Nedlastingar/cx-corpora._2_.text.tmx.gz \ |
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| xmlstarlet sel -t \ |
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-m '//tu[@srclang="da" and tuv/prop/text()="mt" and tuv/@xml:lang="sv"]' \ |
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-c 'tuv[./prop/text()="source"]/seg/text()' -o $'\t' \ |
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-c 'tuv[./prop/text()="mt"]/seg/text()' -o $'\t' \ |
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-c 'tuv[./prop/text()="user"]/seg/text()' -n \ |
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> da2sv.tsv |
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</pre> |
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[[Category:Resources]] |
[[Category:Resources]] |
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[[Category:Development]] |
[[Category:Development]] |
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[[Category:Corpora]] |
[[Category:Corpora]] |
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[[Category:Documentation in English]] |
Latest revision as of 05:40, 10 April 2019
Wikipedia dumps are useful for quickly getting a corpus. They are also the best corpora for making your language pair are useful for Wikipedia's Content Translation tool :-)
You download them from
Tools to turn dumps into plaintext[edit]
There are several tools for turning dumps into useful plaintext, e.g.
- Wikipedia Extractor – a python script that tries to remove all formatting
- wikiextractor – another python script that removes all formatting (with different options), putting XML marks just to know when begins and ends everty single article
- mwdump-to-pandoc – shell wrapper around pandoc (see the usage.sh below the script for how to use)
- Calculating_coverage#More_involved_scripts – an ugly shell script that does the job
- wp2txt – some ruby thing (does this work?)
Content Translation dumps[edit]
There are also dumps of the articles translated with the Content Translation tool, which uses Apertium (and other MT engines) under the hood:
To turn a tmx into a SOURCE\tMT\tGOLD
tab-separated text file, install xmlstarlet (sudo apt install xmlstarlet
) and do:
$ zcat ~/Nedlastingar/cx-corpora.nb2nn.text.tmx.gz \ | xmlstarlet sel -t -m '//tu[tuv/prop/text()="mt"]' \ -c 'tuv[./prop/text()="source"]/seg/text()' -o $'\t' \ -c 'tuv[./prop/text()="mt"]/seg/text()' -o $'\t' \ -c 'tuv[./prop/text()="user"]/seg/text()' -n \ > nb2nn.tsv
Now view the word diff between MT and GOLD with:
$ diff -U0 <(cut -f2 nb2nn.tsv) <(cut -f3 nb2nn.tsv) | dwdiff --diff-input -c | less
and find the original if you need it in cut -f1 nb2nn.tsv
.
For some languages, you have to get the _2CODE files or _2_ files, e.g. sv2da is in https://dumps.wikimedia.org/other/contenttranslation/20180810/cx-corpora._2da.text.tmx.gz and da2sv is in https://dumps.wikimedia.org/other/contenttranslation/20180810/cx-corpora._2_.text.tmx.gz – so let's filter it to the languages we want:
$ zcat ~/Nedlastingar/cx-corpora._2_.text.tmx.gz \ | xmlstarlet sel -t \ -m '//tu[@srclang="da" and tuv/prop/text()="mt" and tuv/@xml:lang="sv"]' \ -c 'tuv[./prop/text()="source"]/seg/text()' -o $'\t' \ -c 'tuv[./prop/text()="mt"]/seg/text()' -o $'\t' \ -c 'tuv[./prop/text()="user"]/seg/text()' -n \ > da2sv.tsv