I am looking for the Sense Id of the word. It has this format here :
http://resources.mpi-inf.mpg.de/yago-naga/yago/download/yago/yagoWordnetIds.txt
On Tue, Sep 8, 2015 at 6:47 PM, Anthony Beylerian <
anthony.beyler...@gmail.com> wrote:
> Hi,
>
> Thanks it is still being improved.
>
> I am not sure what you mean by type or database ID.
> Currently the sense source and the sense ID are returned.
>
> For example:
>
> "I went to the bank to deposit money."
> target : bank (index : 4)
> expected output : [WORDNET bank%1:14:00:: 21.6, WORDNET bank%1:21:01::
> 5.8,... etc]
>
> Where "bank%1:14:00::" is a SenseKey which you can query WordNet with to
> give you a sense definition.
>
> You can do this using the default dictionary :
>
> Dictionary.getDefaultResourceInstance().getWordBySenseKey(sensekey).getSynset().getGloss();
>
> Hope this is what you are looking for, otherwise please clarify.
>
> Anthony Beylerian
>
> On Tue, Sep 8, 2015 at 5:34 PM, Cristian Petroaca <
> cristian.petro...@gmail.com> wrote:
>
> > Hi Anthony,
> >
> > I had a chance to test the wsd component. That's great work. Thanks.
> > One question, is it possible to return the wordnet type (or database id)
> of
> > the disambiguated word?
> >
> > Thanks,
> > Cristian
> >
> > On Fri, Jul 24, 2015 at 1:14 PM, Anthony Beylerian <
> > anthonybeyler...@hotmail.com> wrote:
> >
> > > Hi,
> > >
> > > To try out the ongoing implementations, after checking out the sandbox
> > > repository please try these steps :
> > > 1- Create a resource models directory:
> > >
> > > - src
> > > - test
> > > - resources
> > > + models
> > >
> > > 2- Include the following pre-trained models and dictionary in that
> > > directory:
> > > You can find those here [1] if you like or pre-train your own models.
> > >
> > > {
> > > en-token.bin,
> > > en-pos-maxent.bin,
> > > en-sent.bin,en-ner-person.bin,en-lemmatizer.dict
> > > }
> > >
> > > As to train the IMS approach you need to include training data like
> > > senseval3 [2]:
> > > For now, please add these folders :
> > > - src
> > > - test
> > > - resources
> > > - supervised
> > > + raw
> > > + models
> > > + dictionary
> > >
> > > You can find the data files here [2].
> > >
> > > 3- We included two examples [LeskTester.java] and [IMSTester.java] that
> > > you can run directly, or make your own tests.
> > >
> > > To run a custom test, minimally you need to have a tokenized text or
> > > sentence for example for Lesk:
> > >
> > > 1>> String[] words =
> Loader.getTokenizer().tokenize(sentence);
> > >
> > > Chose the index of the word to disambiguate in the token array.
> > >
> > > 2>> int wordIndex= 6;
> > >
> > > Then just create a WSDisambiguator object for example for Lesk :
> > >
> > > 3>> Lesk lesk = new Lesk();
> > >
> > > And you can call the default disambiguation method
> > >
> > > 4>> lesk.disambiguate(words,wordIndex);
> > >
> > > You will get an array of strings with the following format :
> > >
> > > Lesk : [Source SenseKey Score]
> > >
> > > To read the sense definitions you can use the method :
> > > [opennlp.tools.disambiguator.Constants.printResults]
> > >
> > > For using the variations of Lesk, you will need to create and
> configure a
> > > parameters object:
> > > 5>> LeskParameters leskParams = new LeskParameters();
> > > 6>>
> > >
> leskParams.setLeskType(LeskParameters.LESK_TYPE.LESK_BASIC_CTXT_WIN_BF);
> > > 7>> leskParams.setWin_b_size(4); 8>>
> > > leskParams.setDepth(3); 9>> lesk.setParams(leskParams);
> > >
> > > Typically, IMS should perform better than Lesk, since Lesk is a classic
> > > method but it usually used as a baseline along with the most frequent
> > sense
> > > (MFS).
> > > However, we will be testing and adding more techniques.
> > >
> > > In any case, please feel free to ask for more details.
> > >
> > > Best,
> > >
> > > Anthony
> > >
> > > [1] :
> > >
> >
> https://drive.google.com/folderview?id=0B67Iu3pf6WucfjdYNGhDc3hkTXd1a3FORnNUYzd3dV9YeWlyMFczeHU0SE1TcWwyU1lhZFU&usp=sharing
> > > [2] :
> > >
> >
> https://drive.google.com/file/d/0ByL0dmKXzHVfSXA3SVZiMnVfOGc/view?usp=sharing
> > > > Date: Fri, 24 Jul 2015 09:54:02 +0200
> > > > Subject: Re: Word Sense Disambiguator
> > > > From: kottm...@gmail.com
> > > > To: dev@opennlp.apache.org
> > > >
> > > > It would be nice if you could share instructions on how to run it.
> > > > I also would like to give it a try.
> > > >
> > > > Jörn
> > > >
> > > > On Fri, Jul 24, 2015 at 4:54 AM, Anthony Beylerian <
> > > > anthonybeyler...@hotmail.com> wrote:
> > > >
> > > > > Hello,
> > > > > Yes for the moment we are only using WordNet for sense
> > definitions.The
> > > > > plan is to complete the package by mid to late August, but if you
> > like
> > > you
> > > > > can follow up on the progress from the sandbox.
> > > > > Best regards,
> > > > > Anthony
> > > > > > Date: Thu, 23 Jul 2015 15:36:57 +0300
> > > > > > Subject: Word Sense Disambiguator
> > > > > > From: cristian.petro...@gmail.com
> > > > > > To: dev@opennlp.apache.org
> > > > > >
> > > > > > Hi,
> > > > > >
> > > > > > I saw that there are people actively working on a Word Sense
> > > > > Disambiguator.
> > > > > > DO you guys know when will the module be ready to use? Also I
> > assume
> > > that
> > > > > > wordnet is used to define the disambiguated word meaning?
> > > > > >
> > > > > > Thanks,
> > > > > > Cristian
> > > > >
> > > > >
> > >
> > >
> >
>
