Hi, all,

Thanks for the discussions!

I've merged the code of branches/apertium-swpost/apertium into
trunk/apertium.

Now the Apertium PoS tagger supports both models: HMM and LSW. HMM is the
default choice, and its usage is the same as before. LSW is the new part,
and its usage is also simple: just add an "-w" option while using
apertium-tagger for training, retraining, or tagging.

I've tested the functionalities of HMM in the modifed tagger: unsupervised
training, unsupervised retraining, supervised training, and tagger with
different options. They produced the same result as the original one. The
functionalities of LSW also work as expected.

Any further information, welcome to the wiki page:
http://wiki.apertium.org/w/index.php?title=User:Gang_Chen/GSoC_2013_Progress
If there are any questions/problems about the tagger, please email me :-)

Many thanks to the nice Apertium community!!


Best wishes,
Gang



2013/9/22 Jimmy O'Regan <jore...@gmail.com>

> On 21 September 2013 18:45, Francis Tyers <fty...@prompsit.com> wrote:
> > El ds 21 de 09 de 2013 a les 19:29 +0200, en/na Mikel Forcada va
> > escriure:
> >> Al 09/21/2013 02:11 PM, En/na Francis Tyers ha escrit:
> >> > No, basically I'm asking if it can work without specifying the set of
> >> > coarse tags.
> >> What would happen if one did not specify the set of coarse tags in the
> >> HMM tagger?
> >
> > The main thing is that it would make it easier to train taggers for use
> > after CG. For many language pairs, defining the .tsx file is quite
> > cumbersome if the tagset is large. And with an automatically-defined
> > tagset, the training does not finish because it is too large.
>
> If you had some tagged text, you could treat tag clustering as word
> clustering -- delexicalise the text, generate word classes from it
> (mkcls will do this), and use those as the coarse tags. Here are some
> scripts to do that: https://github.com/jimregan/tag-clusterer
>
> --
> <Sefam> Are any of the mentors around?
> <jimregan> yes, they're the ones trolling you
>
>
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