Tagger training
Creating a corpus
Wikipedia
A basic corpus can be retrieved from Wikipedia as follows:
$ bzcat afwiki-20070508-pages-articles.xml.bz2 | grep '^[A-Z]' | sed 's/$/\n/g' | sed 's/\[\[.*|//g' | sed 's/\]\]//g' | sed 's/\[\[//g' | sed 's/&.*;/ /g' > mycorpus.txt
Other sources
Some pre-processed corpora can be found here and here.
Writing a TSX file
A .tsx
file is a tag definition file, it turns the fine tags from the morphological analyser into course tags for the tagger. The DTD is in tagger.dtd
, although it is probably easier to take a look at one of the pre-written ones in other language pairs.
The file should be in the language pair directory and be called (in for example English-Afrikaans), apertium-en-af.en.tsx
for the English tagger, and apertium-en-af.af.tsx
for the Afrikaans tagger.
Training the tagger
A brief note on the various kinds of training that you can do:
- Unsupervised — This uses a large (hundreds of thousands of words) untagged corpus and the iterative Baum-Welch algorithm in a wholely unsupervised manner.
- Supervised — This uses a medium sized tagged corpus.
- Using
apertium-tagger-trainer
—
Unsupervised
First, make a directory called <lang>-tagger-data
. Put the corpus you downloaded into there with a name like <lang>.crp.txt
. Make sure the corpus is in raw text format with one sentence per line.
Once you have your corpus in there you need a Makefile that specifies how to generate the probability file. You can grab one from another language package. For apertium-en-af
I took the Makefile from apertium-en-ca
. The file that you need is called en-ca-unsupervised.make
.
Copy it into your main language pair directory under an appropriate name, then edit it and change the variables at the top of the file, BASENAME
, LANG1
, and LANG2
. Everything else should be fine.
Now run:
$ make -f en-af-unsupervised.make
and wait... you should get some output like:
Generating en-tagger-data/en.dic This may take some time. Please, take a cup of coffee and come back later. apertium-validate-dictionary apertium-en-af.en.dix apertium-validate-tagger apertium-en-af.en.tsx lt-expand apertium-en-af.en.dix | grep -v "__REGEXP__" | grep -v ":<:" |\ awk 'BEGIN{FS=":>:|:"}{print $1 ".";}' | apertium-destxt >en.dic.expanded lt-proc -a en-af.automorf.bin <en.dic.expanded | \ apertium-filter-ambiguity apertium-en-af.en.tsx > en-tagger-data/en.dic rm en.dic.expanded; apertium-destxt < en-tagger-data/en.crp.txt | lt-proc en-af.automorf.bin > en-tagger-data/en.crp apertium-validate-tagger apertium-en-af.en.tsx apertium-tagger -t 8 \ en-tagger-data/en.dic \ en-tagger-data/en.crp \ apertium-en-af.en.tsx \ en-af.prob; Calculating ambiguity classes... Kupiec's initialization of transition and emission probabilities...
Supervised
Using apertium-tagger-trainer
There is a package called apertium-tagger-trainer
that trains taggers based on both source and target language information. The resulting probability files are as good as supervised training, but much quicker to produce, and with less effort.