Hi Rupert, Thanks again for your suggestions. I cloned and build the stanbol-stanfordnlp project above and executed the run command [1] as below in a separate directory. But the server startup doesn't complete..it hangs at a point with the log entry : "Reading TokensRegex rules from edu/stanford/nlp/models/sutime/english.holidays.sutime.txt"
Any ideas? Can I edit the configurations to skip the above TokenRegex rules and start the server? Thanks, Dileepa [1] dileepa@dileepa-laptop2:~/apache/stanfordNLP_stanbol/server$ *java -Xmx1g -jar at.salzburgresearch.stanbol.stanbol.enhancer.nlp.stanford.server-1.0.0-SNAPSHOT-jar-with-dependencies.jar* Loading default properties from tagger edu/stanford/nlp/models/pos-tagger/english-left3words/english-left3words-distsim.tagger Reading POS tagger model from edu/stanford/nlp/models/pos-tagger/english-left3words/english-left3words-distsim.tagger ... done [2.2 sec]. Loading classifier from edu/stanford/nlp/models/ner/english.all.3class.distsim.crf.ser.gz ... done [6.1 sec]. Loading classifier from edu/stanford/nlp/models/ner/english.conll.4class.distsim.crf.ser.gz ... done [4.3 sec]. Loading classifier from edu/stanford/nlp/models/ner/english.muc.7class.distsim.crf.ser.gz ... done [3.9 sec]. Initialization JollyDayHoliday for sutime Reading TokensRegex rules from edu/stanford/nlp/models/sutime/defs.sutime.txt Reading TokensRegex rules from edu/stanford/nlp/models/sutime/english.sutime.txt Nov 29, 2013 7:14:24 PM edu.stanford.nlp.ling.tokensregex.CoreMapExpressionExtractor appendRules INFO: Ignoring inactive rule: temporal-composite-8:ranges Reading TokensRegex rules from edu/stanford/nlp/models/sutime/english.holidays.sutime.txt On Fri, Nov 29, 2013 at 11:48 AM, Rupert Westenthaler < rupert.westentha...@gmail.com> wrote: > Hi Dileepa > > If you require to detect Entities that are not part of the Controlled > Vocabularies than there is no way around NER. If you want to have good > results there will be no way around of building your own models based > on a custom trainings set. > > If you need to detect Persons, Organizations and Places you might have > a look at Stanford NLP with the Stanbol integration [1]. As the > Stanford Model provided by Stanford NLP is much better as such of > OpenNLP. > > best > Rupert > > > [1] https://github.com/westei/stanbol-stanfordnlp > > On Thu, Nov 28, 2013 at 6:57 AM, Dileepa Jayakody > <dileepajayak...@gmail.com> wrote: > > Hi Rafa, Rupert, > > > > Thanks a lot for your input. I will look at the options you have > suggested. > > However, in the first phase of my project I don't require entity-linking > > from entity-hub because many of the entities mentioned in the content I > > submit will not be available in dbpedia. Therefore currently I also don't > > require dbpediaLinking, entityhubExtraction engines in the default chain > > I'm using. I will look at implementing a custom-vocab in the second phase > > of the project for entity-linking and disambiguation purpose. > > > > At the moment, I focus on improving the accuracy of > > named-entity-recognition using NLP techniques. So I think opennlp-chunker > > based improvements will be very helpful at this point. > > > > Do you think the accuracy of NER will be improved if I also associate > > entitylinking with dbpedia, dbpedia-fst-linking? > > > > Thanks, > > Dileepa > > > > > > On Wed, Nov 27, 2013 at 7:54 PM, Rupert Westenthaler < > > rupert.westentha...@gmail.com> wrote: > > > >> Hi Dileepa, > >> > >> I would suggest you also test with a chain that uses Entity Linking > >> instead of Named Entity Linking. Have you tried the > >> "dbpedia-fst-linking" chain? This one is also configured in the > >> default launcher. Please also have a look at STANBOL-1211 [1] that > >> brought a lot of improvements for EntityLinking if you include a > >> chunker (e.g. the opennlp-chunker) in your chain. > >> > >> best > >> Rupert > >> > >> > >> [1] https://issues.apache.org/jira/browse/STANBOL-1211 > >> > >> On Wed, Nov 27, 2013 at 11:28 AM, Dileepa Jayakody > >> <dileepajayak...@gmail.com> wrote: > >> > Hi Rafa, > >> > > >> > I'm using the default chain; > >> > tika > >> > langdetect > >> > opennlp-sentence > >> > opennlp-token > >> > opennlp-pos > >> > opennlp-ner > >> > dbpediaLinking > >> > entityhubExtraction > >> > > >> > Thanks, > >> > Dileepa > >> > > >> > > >> > On Wed, Nov 27, 2013 at 3:54 PM, Rafa Haro <rh...@apache.org> wrote: > >> > > >> >> Hi Dileepa, > >> >> > >> >> Are you using only OpenNLP NER engine or are you also including an > >> Entity > >> >> Linking engine? > >> >> > >> >> > >> >> El 27/11/13 11:17, Dileepa Jayakody escribió: > >> >> > >> >>> Content: > >> >>> Barclays has appointed Shaygan Kheradpir to the role of Chief > >> Operations > >> >>> and Technology Officer. He will join the Executive Committee of > >> Barclays > >> >>> and report directly to Group Chief Executive Antony Jenkins. > >> >>> > >> >>> Above content doesn't identify* Barclays* as an organization by > >> >>> identifies *Executive > >> >>> Committee of Barclays* as an organization. > >> >>> > >> >>> > >> >>> How can we improve the accuracy of these results? > >> >>> > >> >>> Thanks, > >> >>> Dileepa > >> >>> > >> >>> > >> >>> On Wed, Nov 27, 2013 at 3:42 PM, Dileepa Jayakody < > >> >>> dileepajayak...@gmail.com > >> >>> > >> >>>> wrote: > >> >>>> [Typo corrected in the subject of the mail] > >> >>>> ---------- Forwarded message ---------- > >> >>>> From: Dileepa Jayakody <dileepajayak...@gmail.com> > >> >>>> Date: Wed, Nov 27, 2013 at 3:40 PM > >> >>>> Subject: How to refinin NER results in Stanbol > >> >>>> To: Stanbol Dev List <dev@stanbol.apache.org> > >> >>>> > >> >>>> > >> >>>> Hi All, > >> >>>> > >> >>>> I have been running some load tests on Stanbol entity recognition, > >> with a > >> >>>> high load of content extracted from web articles and stored in a > Solr > >> >>>> index. > >> >>>> > >> >>>> My objective is to achieve an efficient and accurate enhancement > >> result > >> >>>> for the content submitted. > >> >>>> > >> >>>> But I think some of the NER results obtained are not accurate. > >> >>>> > >> >>>> For an example I submit the content : > >> >>>> Group Finance Director Chris Lucas and Group General Counsel Mark > >> Harding > >> >>>> to retire from Barclays > >> >>>> > >> >>>> I get below entity recognition results from default > enhancement-chain; > >> >>>> > >> >>>> People : Chris Lucas, Mark Harding > >> >>>> Organization: Barclays, *BT Group*, *Finance Director Chris Lucas > and > >> >>>> Group General Counsel* > >> >>>> > >> >>>> > >> >>>> The highlighted NERs for organizations above are inaccurate > results. > >> >>>> BT Group is not mentioned in the content, and the result : *Finance > >> >>>> Director Chris Lucas and Group General Counsel * is not an > >> organization, > >> >>>> > >> >>>> rather a phrase. > >> >>>> Further if I add a fullstop (.) to the end of the sentence > "Barclays" > >> is > >> >>>> not recognized as an Organization. > >> >>>> > >> >>>> I think we need to improve these results in Stanbol NER. Can we > tweak > >> >>>> OpenNLP-NER component for this? > >> >>>> > >> >>>> Any ideas/pointers on how to refine these enhancement results will > be > >> >>>> immensely helpful. > >> >>>> I'm looking for a way to improve the accuracy of the results as > much > >> as > >> >>>> possible. > >> >>>> > >> >>>> Thanks, > >> >>>> Dileepa > >> >>>> > >> >>>> > >> >>>> > >> >> > >> > >> > >> > >> -- > >> | Rupert Westenthaler rupert.westentha...@gmail.com > >> | Bodenlehenstraße 11 ++43-699-11108907 > >> | A-5500 Bischofshofen > >> > > > > -- > | Rupert Westenthaler rupert.westentha...@gmail.com > | Bodenlehenstraße 11 ++43-699-11108907 > | A-5500 Bischofshofen >
