The Chunking tool might help here. Chunking means finding noun and
verb phrases. This can help you find recurring phrases. Because German
is agglutinative, this is probably a very different problem than in
English. Are there any de-agglutinizer algorithms?

On Sun, Jun 24, 2012 at 11:43 PM, daniel stieger <[email protected]> wrote:
> Hi,
>
> thanks a lot for your answers. My goal is to identify adjectives and nouns in 
> association sentence. Eg. What do you associate with our brand? Answer: nice 
> mountains, the mountains are very nice .. etc.
>
>
> If appropriate, i would use the openNLP posTagger (it seams to be the most 
> elaborated java postagger) in order to identify nouns and adjectives. So when 
> i input the sentence "the", "mountains", "are", "nice"
> the output is correct - also when using single words:
>
>>> [DT, NNS, VBP, JJ]
>>> [DT]
>>> [NNS]
>>> [VBP]
>>> [JJ]
>
>
> Is the english model better than the german model? Do i have to build my own 
> model - or is the de-maxent appropriate?
>
> Generally - is openNLP a good choice for my task?
>
> Thanks again,
> Dan
>
>
> -------- Original-Nachricht --------
>> Datum: Sat, 23 Jun 2012 16:53:36 -0700
>> Von: Lance Norskog <[email protected]>
>> An: [email protected]
>> Betreff: Re: Newby Question on German POS Tagging
>
>> What would you like to find out about your data? Until we know that it
>> is difficult to recommend a technique.
>>
>> On Sat, Jun 23, 2012 at 4:15 AM, Thilo Goetz <[email protected]> wrote:
>> > On 22.06.2012 20:13, daniel stieger wrote:
>> >>
>> >> Hi List,
>> >>
>> >> i m looking for some suggestions and opinions for my task. The
>> situation
>> >> is this:
>> >>
>> >> In an online survey approx. 800 participants were asked a open text
>> >> question like "What do you associate with our brand?". Participants can
>> then
>> >> enter 5 associations. Eg.
>> >>
>> >>  - nature
>> >>  - beautifull mountains
>> >>  - relax
>> >>  - family friendly
>> >>  - very good service
>> >>
>> >>
>> >> Now i just want to run the openNLP Post tagger over all associations. I
>> >> suppose that i can use one association just as one sentence. Instead of
>> the
>> >> english model, i used the de-maxent.bin model and some german answers.
>> But
>> >> the tags are somehow wrong. Eg.
>> >>
>> >> sonne -> KON
>> >> familie -> ART     (it is a noun, definitely not an aricle)
>> >>
>> >> Am I on a wrong path? Should i handle my data differently? Or should i
>> >> download an other model? Where can i get trainingdata ??
>> >>
>> >> So many questions.. sorry.. but every hint appreciated,
>> >>
>> >> best,
>> >> Daniel
>> >>
>> >>
>> >
>> > I'm pretty sure the model was trained on complete sentences.  The
>> > tagging takes context into account, and will not work properly
>> > without it.  So just running it on a couple of words at a time
>> > will not work.
>> >
>> > If all your associations are NPs like your example,
>> > you can maybe fix things by always prefixing "I like the ".  In
>> > German, maybe "Ich liebe ".
>> >
>> > HTH,
>> > Thilo
>> >
>> >
>>
>>
>>
>> --
>> Lance Norskog
>> [email protected]
>
> --
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-- 
Lance Norskog
[email protected]

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