+1 Maybe we could put the results of the evaluator tests for each component somewhere on a webpage and on every release update them. This is of course provided there are reasonable data sets for testing each component. What do you think?
Anthony > From: mondher.bouaz...@gmail.com > Date: Tue, 21 Jun 2016 15:59:47 +0900 > Subject: Re: Performances of OpenNLP tools > To: dev@opennlp.apache.org > > Hi, > > Thank you for your replies. > > Please Jeffrey accept once more my apologies for receiving the email twice. > > I also think it would be great to have such studies on the performances of > OpenNLP. > > I have been looking for this information and checked in many places, > including obviously google scholar, and I haven't found any serious studies > or reliable results. Most of the existing ones report the performances of > outdated releases of OpenNLP, and focus more on the execution time or > CPU/RAM consumption, etc. > > I think such a comparison will help not only evaluate the overall accuracy, > but also highlight the issues with the existing models (as a matter of > fact, the existing models fail to recognize many of the hashtags in tweets: > the tokenizer splits them into the "#" symbol and a word that the PoS > tagger also fails to recognize). > > Therefore, building Twitter-based models would also be useful, since many > of the works in academia / industry are focusing on Twitter data. > > Best regards, > > Mondher > > > > On Tue, Jun 21, 2016 at 12:45 AM, Jason Baldridge <jasonbaldri...@gmail.com> > wrote: > > > It would be fantastic to have these numbers. This is an example of > > something that would be a great contribution by someone trying to > > contribute to open source and who is maybe just getting into machine > > learning and natural language processing. > > > > For Twitter-ish text, it'd be great to look at models trained and evaluated > > on the Tweet NLP resources: > > > > http://www.cs.cmu.edu/~ark/TweetNLP/ > > > > And comparing to how their models performed, etc. Also, it's worth looking > > at spaCy (Python NLP modules) for further comparisons. > > > > https://spacy.io/ > > > > -Jason > > > > On Mon, 20 Jun 2016 at 10:41 Jeffrey Zemerick <jzemer...@apache.org> > > wrote: > > > > > I saw the same question on the users list on June 17. At least I thought > > it > > > was the same question -- sorry if it wasn't. > > > > > > On Mon, Jun 20, 2016 at 11:37 AM, Mattmann, Chris A (3980) < > > > chris.a.mattm...@jpl.nasa.gov> wrote: > > > > > > > Well, hold on. He sent that mail (as of the time of this mail) 4 > > > > mins previously. Maybe some folks need some time to reply ^_^ > > > > > > > > ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ > > > > Chris Mattmann, Ph.D. > > > > Chief Architect > > > > Instrument Software and Science Data Systems Section (398) > > > > NASA Jet Propulsion Laboratory Pasadena, CA 91109 USA > > > > Office: 168-519, Mailstop: 168-527 > > > > Email: chris.a.mattm...@nasa.gov > > > > WWW: http://sunset.usc.edu/~mattmann/ > > > > ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ > > > > Director, Information Retrieval and Data Science Group (IRDS) > > > > Adjunct Associate Professor, Computer Science Department > > > > University of Southern California, Los Angeles, CA 90089 USA > > > > WWW: http://irds.usc.edu/ > > > > ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > On 6/20/16, 8:23 AM, "Jeffrey Zemerick" <jzemer...@apache.org> wrote: > > > > > > > > >Hi Mondher, > > > > > > > > > >Since you didn't get any replies I'm guessing no one is aware of any > > > > >resources related to what you need. Google Scholar is a good place to > > > look > > > > >for papers referencing OpenNLP and its methods (in case you haven't > > > > >searched it already). > > > > > > > > > >Jeff > > > > > > > > > >On Mon, Jun 20, 2016 at 11:19 AM, Mondher Bouazizi < > > > > >mondher.bouaz...@gmail.com> wrote: > > > > > > > > > >> Hi, > > > > >> > > > > >> Apologies if you received multiple copies of this email. I sent it > > to > > > > the > > > > >> users list a while ago, and haven't had an answer yet. > > > > >> > > > > >> I have been looking for a while if there is any relevant work that > > > > >> performed tests on the OpenNLP tools (in particular the Lemmatizer, > > > > >> Tokenizer and PoS-Tagger) when used with short and noisy texts such > > as > > > > >> Twitter data, etc., and/or compared it to other libraries. > > > > >> > > > > >> By performances, I mean accuracy/precision, rather than time of > > > > execution, > > > > >> etc. > > > > >> > > > > >> If anyone can refer me to a paper or a work done in this context, > > that > > > > >> would be of great help. > > > > >> > > > > >> Thank you very much. > > > > >> > > > > >> Mondher > > > > >> > > > > > > > > >
