Thanks bro
On 6/29/17, 10:52 AM, "Suneel Marthi" <smar...@apache.org> wrote:
http://opennlp.apache.org/docs/1.8.0/manual/opennlp.html#tools.doccat
On Thu, Jun 29, 2017 at 1:51 PM, Chris Mattmann <mattm...@apache.org> wrote:
> Thanks I will investigate the below thanks Joern. Can someone send me some
> pointers
> to the Doc Cat API that I can find? Thanks.
>
>
>
>
> On 6/29/17, 10:18 AM, "Joern Kottmann" <kottm...@gmail.com> wrote:
>
> For 2. I would like to suggest that we implement doccat format support
> to train on that data.
>
> 3. it would be best so think about how we want to test the doccat
> component, today we don't have any tests which use lots of data to
> evaluate it.
> Probably the sentitment data could solve this for us and a train and
> evaluate test could be included in the eval tests.
>
> +1 to revert and then do these steps after the 1.8.1 release.
>
> I can apply my PR myself if nobody objects.
>
> Jörn
>
> On Thu, Jun 29, 2017 at 7:10 PM, Chris Mattmann <mattm...@apache.org>
> wrote:
> > Hi Rodrigo,
> >
> > This is very useful feedback that I wish we would have had a long
> time ago.
> >
> > I will look into it and see if I can reproduce the CLI error. I did
> a full build and mvn
> > install (which I though would run tests?) before commiting and as I
> posted in JIRA
> > the tests passed for me? So I will have to look into that.
> >
> > That said, given your feedback that SentimentME and the Sentiment
> Component
> > doesn’t offer much over Document Classifier I agree with you, but
> wasn’t super
> > familiar with the Document Classifier API. That said, if we can get
> the same functionality
> > by just using Document Classifier why don’t we:
> >
> > 1. Remove the SentimentME and associated code (except for the unit
> tests)
> > 2. Use the sample datasets from NetFlix & Stanford Treebank
> sentiment and
> > build models using Document Classifier API.
> > 3. Rename and keep the unit tests that test against Netflix and
> Stanford tree bank.
> >
> > That way we get basic sentiment analysis (that is working for us
> internally at JPL decently),
> > for Apache OpenNLP, and then if we want to build something better
> than a Document
> > Classification approach to sentiment we can do so.
> >
> > Thoughts?
> >
> > Thanks for your useful feedback. If everyone agrees this is a plan I
> can back out the code
> > using Joern’s revert, and then try and execute 1-3 above in a branch
> first. Thanks.
> >
> > Cheers,
> > Chris
> >
> >
> >
> > On 6/29/17, 10:03 AM, "Rodrigo Agerri" <rage...@apache.org> wrote:
> >
> > Hi Chris,
> >
> > I have been interested in the new sentiment component for a
> while,
> > although truth to be told, I did not follow that closely. I have
> today
> > looked at it and test it with some of the corpora you have
> mentioned.
> > In order to do that, I checkout master to work with from this
> commit
> > onwards
> >
> > https://github.com/apache/opennlp/commit/
> 56321aab51a470cd2004b76fb1f5330881b943c1
> >
> > 1. I tried to run it from the CLI. The Sentiment component did
> not
> > appear to be available.
> > 2. I added the SentimentTrainer and Evaluator to the cmdline.CLI
> (no
> > SentimentTool is implemented to tag with a trained model).
> > 3. After that, the CLI tests did not pass. So, the CLI is
> currently
> > non functional, unless I did something wrong, always possible,
of
> > course. See if you can reproduce that error.
> >
> > I therefore did the tests via API. I implemented a little test
> for
> > training, evaluating and tagging here:
> >
> > https://github.com/ixa-ehu/ixa-pipe-doc/tree/test
> >
> > I run the training on the large movies review from Stanford for
> binary
> > polarity classification
> >
> > http://ai.stanford.edu/~amaas/data/sentiment/
> >
> > and on the two little samples multiclass files added in
> resources and
> > mentioned in the previous email, using the first one for
> training and
> > the second one for testing (maxent 100 iterations, cutoff 5).
> >
> > 2. Stanford results: 0.84264
> > 3. sample multiclass: 0.73
> >
> > Given that this is a standard document classification task, I
> decided
> > to train the doccat component from the CLI:
> >
> > 1. Stanford results: 0.84264 (BOW features by default).
> > 2. sample multiclass: 0.73
> >
> > I then looked at the code of the sentiment component and saw
> that it
> > is basically a document classifier working with bag of words
> features.
> > No added functionality. So, my conclusions are:
> >
> > 1. The CLI needs to be fixed.
> > 2. The Sentiment component, as it is, provides the same
> functionality
> > as the document classifier.
> >
> > I would therefore reconsider this commit until those two issues
> are
> > addressed. Just my opinion.
> >
> > Best regards,
> >
> > Rodrigo
> >
> > On Thu, Jun 29, 2017 at 5:30 PM, Chris Mattmann <
> mattm...@apache.org> wrote:
> > >
> > > Hey Joern,
> > >
> > > Sure, you can find the model data links here, along with our
> evaluation of them.
> > >
> > > http://irds.usc.edu/SentimentAnalysisParser/datasets.html
> > >
> > > There are other evaluations here:
> > >
> > > http://irds.usc.edu/SentimentAnalysisParser/models.html
> > >
> > > The HT provider review I cannot contribute at this time and I
> question its broad
> > > applicability since it’s related to human trafficking. In
> addition we are still working
> > > on publishing our analysis & evaluation of it which is why I
> removed it from the
> > > commit.
> > >
> > > Cheers,
> > > Chris
> > >
> > >
> > >
> > >
> > >
> > > On 6/29/17, 7:36 AM, "Joern Kottmann" <kottm...@gmail.com>
> wrote:
> > >
> > > Which data sets did you use to evaluate this?
> > > I was looking for a bit more than a sample file to train
> it.
> > >
> > > I noticed that you checked in stanford and netflix models.
> > >
> > > The stanford data set is probably this one:
> > > http://ai.stanford.edu/~amaas/data/sentiment/
> > >
> > > Do you have a link for the netflix data?
> > >
> > > Jörn
> > >
> > > On Thu, Jun 29, 2017 at 4:00 PM, Chris Mattmann <
> mattm...@apache.org> wrote:
> > > > Absolutely you can find it here:
> > > >
> > > >
opennlp-tools/src/test/resources/opennlp/tools/sentiment/sample_train_categ
> (for categorical /multi-class)
> > > >
opennlp-tools/src/test/resources/opennlp/tools/sentiment/sample_train_categ2
> (for categorical/multi-class)
> > > >
> > > > We can also do similar files where instead of
> multi-class, we just use pos/neg as the label.
> > > >
> > > > Cheers,
> > > > Chris
> > > >
> > > >
> > > >
> > > >
> > > >
> > > > On 6/29/17, 2:35 AM, "Joern Kottmann" <
> kottm...@gmail.com> wrote:
> > > >
> > > > Hello Chris,
> > > >
> > > > could you please point me to files I can use to
> train the sentiment
> > > > component? I am currently looking again through the
> code and would
> > > > like to train it myself.
> > > >
> > > > Jörn
> > > >
> > > > On Tue, Jun 27, 2017 at 4:59 PM, Dan Russ <
> danrus...@gmail.com> wrote:
> > > > > Hi All,
> > > > > First, let me take a share of blame for the
> comment Chris mentioned. I believe I said something like the pull request
> was X revision behind and Y revisions ahead. It was not meant to be rude,
> it was meant to say it is hard to review code when it is so different from
> the current code base. I am very excited that sentiment analysis is going
> to be added to OpenNLP, but I have not had time to play with it. If I were
> to say “great job” before I have add a chance to look at it, it would be
> flattery not honest praise.
> > > > >
> > > > > Let’s clean up the merge. I agree with Chris
> that scalability and perfection should not be our initial goal. Let’s get
> something, and we can decide how to optimize later (even if it require a
> complete rewrite). Perfection is the enemy of the good.
> > > > >
> > > > > Finally, because of Chris’ comments it is hard
> to thank Ana and Chris without sounding insincere. But I’ll try, thank
you
> Chris and Ana. I hope we can get beyond this and that Chris and Ana will
> continue to improve the performance of the sentiment analysis tool and
> happily remain part of the OpenNLP family. It is also a good time to toss
> a big thank you to all of the committers, users, and PMC member. I use
> OpenNLP almost everyday. Your work is extremely valuable to me.
> > > > >
> > > > > Thank you,
> > > > > Daniel
> > > > >
> > > > >> On Jun 27, 2017, at 10:25 AM, Chris Mattmann <
> mattm...@apache.org> wrote:
> > > > >>
> > > > >> Hi everyone,
> > > > >>
> > > > >> I spoke with Joern in Slack. Some of his concerns
> are:
> > > > >>
> > > > >> 1. This was done with a Merge commit and
> apparently they squash and rebase.
> > > > >> [would be helpful to see some pointer on this for
> documentation, thus far I
> > > > >> haven’t found any]
> > > > >> 2. Apparently we literally need to ask others for
> +1 votes and record them
> > > > >> before committing? I thought since Ana and I are
> committers aren were +1,
> > > > >> and since Joern had been providing feedback (the
> last of which was to add
> > > > >> tests, which we did) that he would be +1 as well
> (I guess he is not, and I guess
> > > > >> formally we need to do a +1 vote even still)
> > > > >> 3. There was concern about scalability of the
> code.
> > > > >> 4. There are thoughts that the code was not
> perfect yet (even though it works
> > > > >> fine in the MEMEX project for Ana and I)
> > > > >>
> > > > >> So, Joern has opened up a revert PR.
> > > > >>
> > > > >> I suppose I should state I find this process
> extremely heavyweight and unwelcoming.
> > > > >> To me, there should be a modicum of trust for
> committers, but I feel like even as a
> > > > >> committer, I am operating as a “contributor” to
> the project. Committer means that
> > > > >> there is trust to modify the source code base. Of
> the issues above, the only one I see
> > > > >> as a moderate snafu was #1, and frankly if there
> are some instructions that show me
> > > > >> how to do squashing and rebasing *first* I will
> try to do that in the future since I am
> > > > >> not a GIt expert.
> > > > >>
> > > > >> That said, I must state I feel pretty put off by
> Apache OpenNLP. This originated as a GSoC
> > > > >> effort, and we have worked pretty consistently on
> this over the last year. We used a
> > > > >> separate GitHub project to get started, kept
> Joern involved as another mentor, even
> > > > >> provided access and commit writes to that GitHub
> repository for a long time, so this
> > > > >> code was developed in the open. Joern even
> created a branch in ApacheOpenNLP in the code and I suppose
> > > > >> I should have gone and worked on that branch
> first since master is apparently so
> > > > >> pristine that even an Apache veteran like me
> can’t get something in to it without
> > > > >> making a whole bunch of (what are IMO minor
> issues, and what are IMO heavyweight
> > > > >> “community” issues).
> > > > >>
> > > > >> I am concerned from a community point of view
> that the first comment wasn’t “Great
> > > > >> job Chris, you got Sentiment Analysis into
> Apache, *but* I have these concerns 1-4 above”.
> > > > >> It was “The PR was merged wrong in ways 1-4 and
> I’m going to revert it.”
> > > > >>
> > > > >> That’s pretty off-putting to someone who is
> semi-new like me and like Ana.
> > > > >>
> > > > >> Anyways, go ahead and revert it. Sorry to have
> caused any issues.
> > > > >>
> > > > >> Chris
> > > > >>
> > > > >>
> > > > >>
> > > > >> On 6/27/17, 7:06 AM, "Chris Mattmann" <
> mattm...@apache.org> wrote:
> > > > >>
> > > > >> Hi Joern,
> > > > >>
> > > > >> I’m confused. Why did you revert my commit?
> > > > >>
> > > > >> Every one of those check points you put on the
> PR was checked?
> > > > >> We have been discussing this for months, you
> have seen the
> > > > >> code for months, Ana and I have worked
> diligently on the code
> > > > >> in plain view of everyone.
> > > > >>
> > > > >> Please explain.
> > > > >>
> > > > >> Chris
> > > > >>
> > > > >>
> > > > >>
> > > > >>
> > > > >> On 6/27/17, 1:23 AM, "kottmann" <
> g...@git.apache.org> wrote:
> > > > >>
> > > > >> GitHub user kottmann opened a pull
request:
> > > > >>
> > > > >> https://github.com/apache/
> opennlp/pull/238
> > > > >>
> > > > >> Revert merging of sentiment work, no
> consent to merge it
> > > > >>
> > > > >> Thank you for contributing to Apache
> OpenNLP.
> > > > >>
> > > > >> In order to streamline the review of
> the contribution we ask you
> > > > >> to ensure the following steps have
> been taken:
> > > > >>
> > > > >> ### For all changes:
> > > > >> - [ ] Is there a JIRA ticket
> associated with this PR? Is it referenced
> > > > >> in the commit message?
> > > > >>
> > > > >> - [ ] Does your PR title start with
> OPENNLP-XXXX where XXXX is the JIRA number you are trying to resolve? Pay
> particular attention to the hyphen "-" character.
> > > > >>
> > > > >> - [ ] Has your PR been rebased against
> the latest commit within the target branch (typically master)?
> > > > >>
> > > > >> - [ ] Is your initial contribution a
> single, squashed commit?
> > > > >>
> > > > >> ### For code changes:
> > > > >> - [ ] Have you ensured that the full
> suite of tests is executed via mvn clean install at the root opennlp
folder?
> > > > >> - [ ] Have you written or updated unit
> tests to verify your changes?
> > > > >> - [ ] If adding new dependencies to
> the code, are these dependencies licensed in a way that is compatible for
> inclusion under [ASF 2.0](http://www.apache.org/
> legal/resolved.html#category-a)?
> > > > >> - [ ] If applicable, have you updated
> the LICENSE file, including the main LICENSE file in opennlp folder?
> > > > >> - [ ] If applicable, have you updated
> the NOTICE file, including the main NOTICE file found in opennlp folder?
> > > > >>
> > > > >> ### For documentation related changes:
> > > > >> - [ ] Have you ensured that format
> looks appropriate for the output in which it is rendered?
> > > > >>
> > > > >> ### Note:
> > > > >> Please ensure that once the PR is
> submitted, you check travis-ci for build issues and submit an update to
> your PR as soon as possible.
> > > > >>
> > > > >>
> > > > >> You can merge this pull request into a Git
> repository by running:
> > > > >>
> > > > >> $ git pull
> https://github.com/kottmann/opennlp revert_sentiment
> > > > >>
> > > > >> Alternatively you can review and apply
> these changes as the patch at:
> > > > >>
> > > > >> https://github.com/apache/
> opennlp/pull/238.patch
> > > > >>
> > > > >> To close this pull request, make a commit
> to your master/trunk branch
> > > > >> with (at least) the following in the
> commit message:
> > > > >>
> > > > >> This closes #238
> > > > >>
> > > > >> ----
> > > > >> commit 123222eb34724bae793e9d6d22e202
> c0aee0aa45
> > > > >> Author: Jörn Kottmann <jo...@apache.org>
> > > > >> Date: 2017-06-27T08:19:19Z
> > > > >>
> > > > >> Revert merging of sentiment work, no
> consent to merge it
> > > > >>
> > > > >> ----
> > > > >>
> > > > >>
> > > > >> ---
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> > > > >>
> > > > >
> > > >
> > > >
> > > >
> > >
> > >
> > >
> >
> >
> >
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