Re: Word sense disambiguation

[Cristian Petroaca]

I know it's not open source. I was referring to replicating their graph
based model using Wordnet.

On Wed, Feb 28, 2018 at 8:47 AM, Rodrigo Agerri 
wrote:

> Hello,
>
> Babelfy is not open source software. DBpedia Spotlight performs Named
> Entity Disambiguation (APL 2.0), UKB (GPL) does WSD and obtains very
> good results, and the IMS system is available for download. There will
> be others, I am sure, but just talking off the top of my head.
>
> HTH
>
> R
>
> On Tue, Feb 27, 2018 at 9:22 PM, Cristian Petroaca
>  wrote:
> > I agree with you. WSD should be included in OpenNLP once it has a
> > reasonably good performance.
> > On the other hand, I have seen few libraries or APIs doing WSD and almost
> > none doing it right. That may be indicative of how hard the problem is.
> >
> > The only promising api I found is Babelfy : http://babelfy.org/about. It
> > uses a graph based model based on their BabelNet Knowledge base in order
> to
> > predict word senses. I think it's based on this paper:
> > http://www.aclweb.org/anthology/Q14-1019. Any thoughts on this?
> >
> > On Sat, Feb 24, 2018 at 7:49 PM, Anthony Beylerian <
> > anthony.beyler...@gmail.com> wrote:
> >
> >> Hey Cristian,
> >>
> >> We have tried different approaches such as:
> >>
> >> - Lesk (original) [1]
> >> - Most frequent sense from the data (MFS)
> >> - Extended Lesk (with different scoring functions)
> >> - It makes sense (IMS) [2]
> >> - A sense clustering approach (I don't immediately recall the reference)
> >>
> >> Lesk and MFS are meant to be used as baselines for evaluation purpose
> only.
> >> The extended version of Lesk is an effort to improve the original,
> through
> >> additional information from semantic relationships.
> >> Although it's not very accurate, it could be useful since it is an
> >> unsupervised method (no need for large training data).
> >> However, there were some caveats, as both approaches need to pre-load
> >> dictionaries as well as score a semantic graph from WordNet at runtime.
> >>
> >> IMS is a supervised method which we were hoping to mainly use, since it
> >> scored around 80% accuracy on SemEval, however that is only for the
> >> coarse-grained case. However, in reality words have various degrees of
> >> polysemy, and when tested in the fine-grained case the results were much
> >> lower.
> >> We have also experimented with a simple clustering approach but the
> >> improvements were not considerable as far as I remember.
> >>
> >> I just checked the latest results on Semeval2015 [3] and they look a bit
> >> improved on the fine-grained case ~65% F1.
> >> However, in some particular domains it looks like the accuracy
> increases,
> >> so it could depend on the use case.
> >>
> >> On the other hand, there could be some more recent studies that could
> yield
> >> better results, but that would need some more investigation.
> >>
> >> There are also some other issues such as lack of direct multi-lingual
> >> support from WordNet, missing sense definitions etc.
> >> We were also still looking for a better source of sense definitions back
> >> then.
> >> In any case, I believe it would be better to have higher performance
> before
> >> putting this in the official distribution, however that highly depends
> on
> >> the team.
> >> Otherwise, different parts of the code just need some simple
> refactoring as
> >> well.
> >>
> >> Best,
> >>
> >> Anthony
> >>
> >> [1] : M. Lesk, Automatic sense disambiguation using machine readable
> >> dictionaries
> >> [2] : https://www.comp.nus.edu.sg/~nght/pubs/ims.pdf
> >> [3] : http://alt.qcri.org/semeval2015/task13/index.php?id=results
> >>
> >> On Wed, Feb 21, 2018 at 5:26 AM, Cristian Petroaca <
> >> cristian.petro...@gmail.com> wrote:
> >>
> >> > Hi Anthony,
> >> >
> >> > I'd be interested to discuss this further.
> >> > What are the wsd methods used? Any links to papers?
> >> > How does the module perform when being evaluated against Senseval?
> >> >
> >> > How much work do you think it's necessary in order to have a
> functioning
> >> > WSD module in the context of OpenNLP?
> >> >
> >> > Thanks,
> >> > Cristian
> >> >
> >> >
> >> >
> >> > On Tue, Feb 20, 2018 at 8:09 AM, Anthony Beylerian <
> >> > anthony.beyler...@gmail.com> wrote:
> >> >
> >> >> Hi Cristian,
> >> >>
> >> >> Thank you for your interest.
> >> >>
> >> >> The WSD module is currently experimental, so as far as I am aware
> there
> >> >> is no timeline for it.
> >> >>
> >> >> You can find the sandboxed version here:
> >> >> https://github.com/apache/opennlp-sandbox/tree/master/opennlp-wsd
> >> >>
> >> >> I personally didn't have the time to revisit this for a while and
> there
> >> >> are still some details to work out.
> >> >> But if you are really interested, you are welcome to discuss and
> >> >> contribute.
> >> >> I will assist as much as possible.
> >> >>
> >> >> Best,
> >> >>
> >> >> Anthony
> >> >>
> >> >> On Sun, Feb 18, 2018 at 5:52 AM, Cristian 

Re: Word sense disambiguation

[Rodrigo Agerri]

Hello,

Babelfy is not open source software. DBpedia Spotlight performs Named
Entity Disambiguation (APL 2.0), UKB (GPL) does WSD and obtains very
good results, and the IMS system is available for download. There will
be others, I am sure, but just talking off the top of my head.

HTH

R

On Tue, Feb 27, 2018 at 9:22 PM, Cristian Petroaca
 wrote:
> I agree with you. WSD should be included in OpenNLP once it has a
> reasonably good performance.
> On the other hand, I have seen few libraries or APIs doing WSD and almost
> none doing it right. That may be indicative of how hard the problem is.
>
> The only promising api I found is Babelfy : http://babelfy.org/about. It
> uses a graph based model based on their BabelNet Knowledge base in order to
> predict word senses. I think it's based on this paper:
> http://www.aclweb.org/anthology/Q14-1019. Any thoughts on this?
>
> On Sat, Feb 24, 2018 at 7:49 PM, Anthony Beylerian <
> anthony.beyler...@gmail.com> wrote:
>
>> Hey Cristian,
>>
>> We have tried different approaches such as:
>>
>> - Lesk (original) [1]
>> - Most frequent sense from the data (MFS)
>> - Extended Lesk (with different scoring functions)
>> - It makes sense (IMS) [2]
>> - A sense clustering approach (I don't immediately recall the reference)
>>
>> Lesk and MFS are meant to be used as baselines for evaluation purpose only.
>> The extended version of Lesk is an effort to improve the original, through
>> additional information from semantic relationships.
>> Although it's not very accurate, it could be useful since it is an
>> unsupervised method (no need for large training data).
>> However, there were some caveats, as both approaches need to pre-load
>> dictionaries as well as score a semantic graph from WordNet at runtime.
>>
>> IMS is a supervised method which we were hoping to mainly use, since it
>> scored around 80% accuracy on SemEval, however that is only for the
>> coarse-grained case. However, in reality words have various degrees of
>> polysemy, and when tested in the fine-grained case the results were much
>> lower.
>> We have also experimented with a simple clustering approach but the
>> improvements were not considerable as far as I remember.
>>
>> I just checked the latest results on Semeval2015 [3] and they look a bit
>> improved on the fine-grained case ~65% F1.
>> However, in some particular domains it looks like the accuracy increases,
>> so it could depend on the use case.
>>
>> On the other hand, there could be some more recent studies that could yield
>> better results, but that would need some more investigation.
>>
>> There are also some other issues such as lack of direct multi-lingual
>> support from WordNet, missing sense definitions etc.
>> We were also still looking for a better source of sense definitions back
>> then.
>> In any case, I believe it would be better to have higher performance before
>> putting this in the official distribution, however that highly depends on
>> the team.
>> Otherwise, different parts of the code just need some simple refactoring as
>> well.
>>
>> Best,
>>
>> Anthony
>>
>> [1] : M. Lesk, Automatic sense disambiguation using machine readable
>> dictionaries
>> [2] : https://www.comp.nus.edu.sg/~nght/pubs/ims.pdf
>> [3] : http://alt.qcri.org/semeval2015/task13/index.php?id=results
>>
>> On Wed, Feb 21, 2018 at 5:26 AM, Cristian Petroaca <
>> cristian.petro...@gmail.com> wrote:
>>
>> > Hi Anthony,
>> >
>> > I'd be interested to discuss this further.
>> > What are the wsd methods used? Any links to papers?
>> > How does the module perform when being evaluated against Senseval?
>> >
>> > How much work do you think it's necessary in order to have a functioning
>> > WSD module in the context of OpenNLP?
>> >
>> > Thanks,
>> > Cristian
>> >
>> >
>> >
>> > On Tue, Feb 20, 2018 at 8:09 AM, Anthony Beylerian <
>> > anthony.beyler...@gmail.com> wrote:
>> >
>> >> Hi Cristian,
>> >>
>> >> Thank you for your interest.
>> >>
>> >> The WSD module is currently experimental, so as far as I am aware there
>> >> is no timeline for it.
>> >>
>> >> You can find the sandboxed version here:
>> >> https://github.com/apache/opennlp-sandbox/tree/master/opennlp-wsd
>> >>
>> >> I personally didn't have the time to revisit this for a while and there
>> >> are still some details to work out.
>> >> But if you are really interested, you are welcome to discuss and
>> >> contribute.
>> >> I will assist as much as possible.
>> >>
>> >> Best,
>> >>
>> >> Anthony
>> >>
>> >> On Sun, Feb 18, 2018 at 5:52 AM, Cristian Petroaca <
>> >> cristian.petro...@gmail.com> wrote:
>> >>
>> >>> Hi,
>> >>>
>> >>> I'm interested in word sense disambiguation (particularly based on
>> >>> Wordnet). I noticed that the latest OpenNLP version doesn't have any
>> but
>> >>> I
>> >>> remember that a couple of years ago there was somebody working on
>> >>> implementing it. Why isn't it in the official OpenNLP jar? Is there a
>> >>> timeline for adding it?
>> >>>
>> >>> 

Re: Word sense disambiguation

[Cristian Petroaca]

I agree with you. WSD should be included in OpenNLP once it has a
reasonably good performance.
On the other hand, I have seen few libraries or APIs doing WSD and almost
none doing it right. That may be indicative of how hard the problem is.

The only promising api I found is Babelfy : http://babelfy.org/about. It
uses a graph based model based on their BabelNet Knowledge base in order to
predict word senses. I think it's based on this paper:
http://www.aclweb.org/anthology/Q14-1019. Any thoughts on this?

On Sat, Feb 24, 2018 at 7:49 PM, Anthony Beylerian <
anthony.beyler...@gmail.com> wrote:

> Hey Cristian,
>
> We have tried different approaches such as:
>
> - Lesk (original) [1]
> - Most frequent sense from the data (MFS)
> - Extended Lesk (with different scoring functions)
> - It makes sense (IMS) [2]
> - A sense clustering approach (I don't immediately recall the reference)
>
> Lesk and MFS are meant to be used as baselines for evaluation purpose only.
> The extended version of Lesk is an effort to improve the original, through
> additional information from semantic relationships.
> Although it's not very accurate, it could be useful since it is an
> unsupervised method (no need for large training data).
> However, there were some caveats, as both approaches need to pre-load
> dictionaries as well as score a semantic graph from WordNet at runtime.
>
> IMS is a supervised method which we were hoping to mainly use, since it
> scored around 80% accuracy on SemEval, however that is only for the
> coarse-grained case. However, in reality words have various degrees of
> polysemy, and when tested in the fine-grained case the results were much
> lower.
> We have also experimented with a simple clustering approach but the
> improvements were not considerable as far as I remember.
>
> I just checked the latest results on Semeval2015 [3] and they look a bit
> improved on the fine-grained case ~65% F1.
> However, in some particular domains it looks like the accuracy increases,
> so it could depend on the use case.
>
> On the other hand, there could be some more recent studies that could yield
> better results, but that would need some more investigation.
>
> There are also some other issues such as lack of direct multi-lingual
> support from WordNet, missing sense definitions etc.
> We were also still looking for a better source of sense definitions back
> then.
> In any case, I believe it would be better to have higher performance before
> putting this in the official distribution, however that highly depends on
> the team.
> Otherwise, different parts of the code just need some simple refactoring as
> well.
>
> Best,
>
> Anthony
>
> [1] : M. Lesk, Automatic sense disambiguation using machine readable
> dictionaries
> [2] : https://www.comp.nus.edu.sg/~nght/pubs/ims.pdf
> [3] : http://alt.qcri.org/semeval2015/task13/index.php?id=results
>
> On Wed, Feb 21, 2018 at 5:26 AM, Cristian Petroaca <
> cristian.petro...@gmail.com> wrote:
>
> > Hi Anthony,
> >
> > I'd be interested to discuss this further.
> > What are the wsd methods used? Any links to papers?
> > How does the module perform when being evaluated against Senseval?
> >
> > How much work do you think it's necessary in order to have a functioning
> > WSD module in the context of OpenNLP?
> >
> > Thanks,
> > Cristian
> >
> >
> >
> > On Tue, Feb 20, 2018 at 8:09 AM, Anthony Beylerian <
> > anthony.beyler...@gmail.com> wrote:
> >
> >> Hi Cristian,
> >>
> >> Thank you for your interest.
> >>
> >> The WSD module is currently experimental, so as far as I am aware there
> >> is no timeline for it.
> >>
> >> You can find the sandboxed version here:
> >> https://github.com/apache/opennlp-sandbox/tree/master/opennlp-wsd
> >>
> >> I personally didn't have the time to revisit this for a while and there
> >> are still some details to work out.
> >> But if you are really interested, you are welcome to discuss and
> >> contribute.
> >> I will assist as much as possible.
> >>
> >> Best,
> >>
> >> Anthony
> >>
> >> On Sun, Feb 18, 2018 at 5:52 AM, Cristian Petroaca <
> >> cristian.petro...@gmail.com> wrote:
> >>
> >>> Hi,
> >>>
> >>> I'm interested in word sense disambiguation (particularly based on
> >>> Wordnet). I noticed that the latest OpenNLP version doesn't have any
> but
> >>> I
> >>> remember that a couple of years ago there was somebody working on
> >>> implementing it. Why isn't it in the official OpenNLP jar? Is there a
> >>> timeline for adding it?
> >>>
> >>> Thanks,
> >>> Cristian
> >>>
> >>
> >>
> >
>

Re: Word sense disambiguation

[Cristian Petroaca]

Hi Anthony,

I'd be interested to discuss this further.
What are the wsd methods used? Any links to papers?
How does the module perform when being evaluated against Senseval?

How much work do you think it's necessary in order to have a functioning
WSD module in the context of OpenNLP?

Thanks,
Cristian



On Tue, Feb 20, 2018 at 8:09 AM, Anthony Beylerian <
anthony.beyler...@gmail.com> wrote:

> Hi Cristian,
>
> Thank you for your interest.
>
> The WSD module is currently experimental, so as far as I am aware there
> is no timeline for it.
>
> You can find the sandboxed version here:
> https://github.com/apache/opennlp-sandbox/tree/master/opennlp-wsd
>
> I personally didn't have the time to revisit this for a while and there
> are still some details to work out.
> But if you are really interested, you are welcome to discuss and
> contribute.
> I will assist as much as possible.
>
> Best,
>
> Anthony
>
> On Sun, Feb 18, 2018 at 5:52 AM, Cristian Petroaca <
> cristian.petro...@gmail.com> wrote:
>
>> Hi,
>>
>> I'm interested in word sense disambiguation (particularly based on
>> Wordnet). I noticed that the latest OpenNLP version doesn't have any but I
>> remember that a couple of years ago there was somebody working on
>> implementing it. Why isn't it in the official OpenNLP jar? Is there a
>> timeline for adding it?
>>
>> Thanks,
>> Cristian
>>
>
>

Re: Word sense disambiguation

[Anthony Beylerian]

Hi Cristian,

Thank you for your interest.

The WSD module is currently experimental, so as far as I am aware there is
no timeline for it.

You can find the sandboxed version here:
https://github.com/apache/opennlp-sandbox/tree/master/opennlp-wsd

I personally didn't have the time to revisit this for a while and there are
still some details to work out.
But if you are really interested, you are welcome to discuss and contribute.
I will assist as much as possible.

Best,

Anthony

On Sun, Feb 18, 2018 at 5:52 AM, Cristian Petroaca <
cristian.petro...@gmail.com> wrote:

> Hi,
>
> I'm interested in word sense disambiguation (particularly based on
> Wordnet). I noticed that the latest OpenNLP version doesn't have any but I
> remember that a couple of years ago there was somebody working on
> implementing it. Why isn't it in the official OpenNLP jar? Is there a
> timeline for adding it?
>
> Thanks,
> Cristian
>

RE: Word Sense Disambiguation

[Anthony Beylerian]

Thank you for the feedback, I believe that having separate interfaces as 
mentioned for sense provision and disambiguation would be a good idea. 
We will try to survey the techniques and study the library further to propose a 
first structure when possible.
Best,

Anthony
 Subject: Re: Word Sense Disambiguation
 From: kottm...@gmail.com
 To: dev@opennlp.apache.org
 Date: Mon, 16 Feb 2015 16:48:48 +0100
 
 On Mon, 2015-02-16 at 16:29 +0100, Aliaksandr Autayeu wrote:
  Jörn, to avoid ambiguity in case you addressed me to propose a WSD
  interface. I'd prefer Anthony to come up with a proposal, because he is
  closer to the multiple WSD algorithms that would be nice to include in the
  analysis.
 
 Sorry, for being unclear, yes I addressed Anthony. But everybody who has
 an opinion is very welcome to join the discussion or propose something.
 
 Jörn
 

  

Re: Word Sense Disambiguation

[Aliaksandr Autayeu]

One more observation. The interfaces might depend on whether the sense
source includes proper nouns (entities) or not. For example, WordNet
includes some small, but noticeable amount (~8000 if I'm not mistaken) of
entities. It might be better to separate the two, it might be not - it
depends. But the interfaces might depend on this assumption. And
considering entities in WSD the situation becomes close (similar) to NER.
It would be great if you take this into account and make assumptions
explicit. It would be also great to discuss your findings in the state of
the art of interfaces for WSD and sense (entity) sources.

Aliaksandr

On 18 February 2015 at 14:39, Anthony Beylerian 
anthonybeyler...@hotmail.com wrote:




 Thank you for the feedback, I believe that having separate interfaces as
 mentioned for sense provision and disambiguation would be a good idea.
 We will try to survey the techniques and study the library further to
 propose a first structure when possible.
 Best,

 Anthony
  Subject: Re: Word Sense Disambiguation
  From: kottm...@gmail.com
  To: dev@opennlp.apache.org
  Date: Mon, 16 Feb 2015 16:48:48 +0100
 
  On Mon, 2015-02-16 at 16:29 +0100, Aliaksandr Autayeu wrote:
   Jörn, to avoid ambiguity in case you addressed me to propose a WSD
   interface. I'd prefer Anthony to come up with a proposal, because he is
   closer to the multiple WSD algorithms that would be nice to include in
 the
   analysis.
 
  Sorry, for being unclear, yes I addressed Anthony. But everybody who has
  an opinion is very welcome to join the discussion or propose something.
 
  Jörn
 

Re: Word Sense Disambiguation

[Joern Kottmann]

On Mon, 2015-02-16 at 16:29 +0100, Aliaksandr Autayeu wrote:
 Jörn, to avoid ambiguity in case you addressed me to propose a WSD
 interface. I'd prefer Anthony to come up with a proposal, because he is
 closer to the multiple WSD algorithms that would be nice to include in the
 analysis.

Sorry, for being unclear, yes I addressed Anthony. But everybody who has
an opinion is very welcome to join the discussion or propose something.

Jörn

Re: Word Sense Disambiguation

[Aliaksandr Autayeu]

Jörn, to avoid ambiguity in case you addressed me to propose a WSD
interface. I'd prefer Anthony to come up with a proposal, because he is
closer to the multiple WSD algorithms that would be nice to include in the
analysis.

Aliaksandr

On 16 February 2015 at 15:19, Joern Kottmann kottm...@gmail.com wrote:

 On Sat, 2015-02-14 at 11:09 +0100, Aliaksandr Autayeu wrote:
  Since you're perhaps deeper in this that others you seem to be the
  best
  candidate to make a proposal, to check the state of the art algorithms
  and
  devise general enough interface for all or most of them. One way could
  be
  to see what the algorithms typically require, how diverse are sources
  of
  senses (WordNet alone has multiple different interfaces to access it),
  which options do the algorithms take and start somewhere there to see
  that
  the interface is flexible enough to accommodate that diversity, has
  ability
  to do some built-in checks (such as detecting the case of algorithm
  trained
  on one source of senses working with another, or perhaps algorithm
  relying
  on a relation which is missing in the sense source) and be similar to
  the
  rest of OpenNLP. We might even end up with two interfaces (e.g. for
  sense
  provider and for WSD itself).
 
  What do you think about this way?

 Please propose an interface. We will discuss it here on the list.

 Jörn

RE: Word Sense Disambiguation

[Anthony Beylerian]

Dear devs,

Please try some of the few (simpler) algorithms we implemented to warm up to 
the library :
http://131.113.41.202:8080/opennlp-wsd-demo/nlp-wsd-fe/app/#/home
(will make the source available after cleanup/housekeeping)

We need to define the structure and method signatures, since we will later 
increment with more techniques.

Any suggestions/references for the structure and signatures are welcome.
Best,

Anthony

 Subject: Re: Word Sense Disambiguation
 From: kottm...@gmail.com
 To: dev@opennlp.apache.org
 Date: Mon, 19 Jan 2015 19:10:19 +0100
 
 Hello,
 
 +1 from me to just go ahead and implement the proposed approach. One
 goal of this implementation will be to figure out the interface we want
 to have in OpenNLP for WSD.
 
 We can later extend OpenNLP with more implementations which are taking
 different approaches.
 
 Jörn
 
 On Thu, 2015-01-15 at 16:50 +0900, Anthony Beylerian wrote:
  Hello, 
  
  I'm new here, I previously mentioned to Jörn about my colleagues and myself 
  being interested in helping to implement this component, we were thinking 
  of starting with simple knowledge based approaches, although they do not 
  yield high accuracy, but as a first step they are relatively simple, would 
  like your opinion.
  
  Pei also mentioned cTAKES 
  (http://svn.apache.org/repos/asf/ctakes/sandbox/ctakes-wsd/ currently very 
  exploratory stages here) and YTEX 
  (https://code.google.com/p/ytex/wiki/WordSenseDisambiguation_V08) is also 
  just exploring WSD for the healthcare domain. It's also currently 
  knowledge/ontology base for now... It would be great to see if OpenNLP 
  supports a general domain WSD
  
  Best, 
  
  Anthony

 
 
  

Re: Word Sense Disambiguation

[Aliaksandr Autayeu]

Anthony, the app looks really nice and neat! But I wonder what is the
intended benefit of us trying the algorithms? To have a subjective
impression? Let me know, maybe I missed something.

Maybe it is better to link to papers with evaluation of the algorithms you
implement? Maybe even better to test your implementations on a public
sense-tagged corpus and post the evaluation results here? And maybe compare
these evaluations with peer-reviewed ones in the literature, thus making
sure your implementation is in line? What do you think? Do you think it is
feasible you do that? Any volunteers to do that?

Aliaksandr

On 13 February 2015 at 10:12, Anthony Beylerian 
anthonybeyler...@hotmail.com wrote:

 Dear devs,

 Please try some of the few (simpler) algorithms we implemented to warm up
 to the library :
 http://131.113.41.202:8080/opennlp-wsd-demo/nlp-wsd-fe/app/#/home
 (will make the source available after cleanup/housekeeping)

 We need to define the structure and method signatures, since we will later
 increment with more techniques.

 Any suggestions/references for the structure and signatures are welcome.
 Best,

 Anthony

  Subject: Re: Word Sense Disambiguation
  From: kottm...@gmail.com
  To: dev@opennlp.apache.org
  Date: Mon, 19 Jan 2015 19:10:19 +0100
 
  Hello,
 
  +1 from me to just go ahead and implement the proposed approach. One
  goal of this implementation will be to figure out the interface we want
  to have in OpenNLP for WSD.
 
  We can later extend OpenNLP with more implementations which are taking
  different approaches.
 
  Jörn
 
  On Thu, 2015-01-15 at 16:50 +0900, Anthony Beylerian wrote:
   Hello,
  
   I'm new here, I previously mentioned to Jörn about my colleagues and
 myself being interested in helping to implement this component, we were
 thinking of starting with simple knowledge based approaches, although they
 do not yield high accuracy, but as a first step they are relatively simple,
 would like your opinion.
  
   Pei also mentioned cTAKES (
 http://svn.apache.org/repos/asf/ctakes/sandbox/ctakes-wsd/ currently very
 exploratory stages here) and YTEX (
 https://code.google.com/p/ytex/wiki/WordSenseDisambiguation_V08) is also
 just exploring WSD for the healthcare domain. It's also currently
 knowledge/ontology base for now... It would be great to see if OpenNLP
 supports a general domain WSD
  
   Best,
  
   Anthony
  
 
 

Re: Word Sense Disambiguation

[Rodrigo Agerri]

+1

On Mon, Jan 19, 2015 at 10:30 PM, Mark G ma...@apache.org wrote:
 +1

 On Mon, Jan 19, 2015 at 1:49 PM, Tommaso Teofili tommaso.teof...@gmail.com
 wrote:

 +1

 Tommaso

 2015-01-19 19:10 GMT+01:00 Joern Kottmann kottm...@gmail.com:

  Hello,
 
  +1 from me to just go ahead and implement the proposed approach. One
  goal of this implementation will be to figure out the interface we want
  to have in OpenNLP for WSD.
 
  We can later extend OpenNLP with more implementations which are taking
  different approaches.
 
  Jörn
 
  On Thu, 2015-01-15 at 16:50 +0900, Anthony Beylerian wrote:
   Hello,
  
   I'm new here, I previously mentioned to Jörn about my colleagues and
  myself being interested in helping to implement this component, we were
  thinking of starting with simple knowledge based approaches, although
 they
  do not yield high accuracy, but as a first step they are relatively
 simple,
  would like your opinion.
  
   Pei also mentioned cTAKES (
  http://svn.apache.org/repos/asf/ctakes/sandbox/ctakes-wsd/ currently
 very
  exploratory stages here) and YTEX (
  https://code.google.com/p/ytex/wiki/WordSenseDisambiguation_V08) is also
  just exploring WSD for the healthcare domain. It's also currently
  knowledge/ontology base for now... It would be great to see if OpenNLP
  supports a general domain WSD
  
   Best,
  
   Anthony
  
 
 
 

Re: Word Sense Disambiguation

[Joern Kottmann]

Hello,

+1 from me to just go ahead and implement the proposed approach. One
goal of this implementation will be to figure out the interface we want
to have in OpenNLP for WSD.

We can later extend OpenNLP with more implementations which are taking
different approaches.

Jörn

On Thu, 2015-01-15 at 16:50 +0900, Anthony Beylerian wrote:
 Hello, 
 
 I'm new here, I previously mentioned to Jörn about my colleagues and myself 
 being interested in helping to implement this component, we were thinking of 
 starting with simple knowledge based approaches, although they do not yield 
 high accuracy, but as a first step they are relatively simple, would like 
 your opinion.
 
 Pei also mentioned cTAKES 
 (http://svn.apache.org/repos/asf/ctakes/sandbox/ctakes-wsd/ currently very 
 exploratory stages here) and YTEX 
 (https://code.google.com/p/ytex/wiki/WordSenseDisambiguation_V08) is also 
 just exploring WSD for the healthcare domain. It's also currently 
 knowledge/ontology base for now... It would be great to see if OpenNLP 
 supports a general domain WSD
 
 Best, 
 
 Anthony
 

Re: Word Sense Disambiguation

[Tommaso Teofili]

+1

Tommaso

2015-01-19 19:10 GMT+01:00 Joern Kottmann kottm...@gmail.com:

 Hello,

 +1 from me to just go ahead and implement the proposed approach. One
 goal of this implementation will be to figure out the interface we want
 to have in OpenNLP for WSD.

 We can later extend OpenNLP with more implementations which are taking
 different approaches.

 Jörn

 On Thu, 2015-01-15 at 16:50 +0900, Anthony Beylerian wrote:
  Hello,
 
  I'm new here, I previously mentioned to Jörn about my colleagues and
 myself being interested in helping to implement this component, we were
 thinking of starting with simple knowledge based approaches, although they
 do not yield high accuracy, but as a first step they are relatively simple,
 would like your opinion.
 
  Pei also mentioned cTAKES (
 http://svn.apache.org/repos/asf/ctakes/sandbox/ctakes-wsd/ currently very
 exploratory stages here) and YTEX (
 https://code.google.com/p/ytex/wiki/WordSenseDisambiguation_V08) is also
 just exploring WSD for the healthcare domain. It's also currently
 knowledge/ontology base for now... It would be great to see if OpenNLP
 supports a general domain WSD
 
  Best,
 
  Anthony