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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