Great! Please add your language and stopwords (+ maybe other resources such
as the tokenizer) to the following repository:
https://github.com/dbpedia-spotlight/model-quickstarter
You can send a pull request on github.
Jo
On Thu, Jan 30, 2014 at 9:06 AM, [email protected] <
[email protected]> wrote:
> Thanks! I think that dictionary-based model will be enough for now. In
> the future we will retrain the OpenNLP models for better performance.
>
> Even so the basque Wikipedia is too small :(
>
> best,
>
> ander
>
>
>
> az., 2014.eko urtren 29a 22:07(e)an, Joachim Daiber(e)k idatzi zuen:
>
> Hi Ander,
>
> the statistical backend currently only supports OpenNLP models. This is
> simply because they were readily available. So from my point of view there
> are 2 things you can do:
>
> 1. change Spotlight to additionally accept your tool (assuming it's JVM
> based)
> 2. retrain your models with OpenNLP
>
> But regardless, you do not need those necessarily. If you do not provide
> the models to the training, the statistical backend will learn a
> dictionary-based spotting model. Depending on the size of the Wikipedia
> input, this should work equally well (if the Wikipedia is too small, it
> might be a bit sparse).
>
> Hope that helps,
> Jo
>
>
>
>
>
>
> On Wed, Jan 29, 2014 at 3:11 PM, [email protected] <
> [email protected]> wrote:
>
>> Hi spotlight users,
>>
>> Our main idea is to apply NED in basque documents, for this proposal, we
>> want to use the dbpedia spotlight statistical backend system.
>>
>> We want to create a Spotlight model for Basque language, but we have a
>> "little" problem. We have seen that there isn't any openNLP model for
>> Basque. We have all the resources such as tokenizer, chuncker, POS
>> tagger, stopwords... but not any of the openNLP pre-trained models for
>> this language.
>>
>> Our questions are:
>>
>> Is there any other way to use this resources instead of using openNLP
>> models? For example, integrating our resources in the system code and
>> giving the output to dbpedia spotlight system (without openNLP models).
>> Does someone done something like this before?
>> Or
>> Do we need to build an openNLP model compulsorily?
>>
>> thanks in advance,
>>
>> Ander
>>
>>
>>
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