Yes James, I believe that is still true for POS tags, maybe for chunks. Thanks for pointing out that complication. Tim
On 05/19/2015 12:52 PM, Masanz, James J. wrote: > Damir, > > Be aware the original POS and chunker models in cTAKES were built using text > tokenized the way cTAKES tokenizes text. That might not work as well on text > tokenized using a different method. > > Tim, is that still true of the current POS models in Apache cTAKES? > > -- James > > -----Original Message----- > From: Damir Olejar [mailto:[email protected]] > Sent: Tuesday, May 19, 2015 10:03 AM > To: [email protected] > Subject: Re: OpenNLP VS UIMA, general question. > > Yes, that is exactly what I was asking! > Thank you, and sorry for not being more thorough with the questions, as I > am new to cTakes. > > Damir > > On Tue, May 19, 2015 at 10:51 AM, Miller, Timothy < > [email protected]> wrote: > >> I'm not totally sure I understand your question. But if you are asking >> if it's possible to use the clinical-trained OpenNLP models released >> with cTAKES without using UIMA, yes, it should be possible. Some of the >> cTAKES modules simply wrap OpenNLP APIs, and convert the >> POS-tagged/Chunked/Parsed output into the UIMA typesystem. >> >> Or are you asking if you can write a UIMA annotator that consumes >> OpenNLP annotations rather than cTAKES' UIMA-based annotations? That is >> possible too, though would definitely add complexity to a UIMA pipeline. >> >> Tim >> >> On 05/19/2015 10:08 AM, Damir Olejar wrote: >>> To whom it may concern, >>> >>> I would like to ask whether it is possible to have a code written for >>> OpenNLP and then, if necessary, integrate it with UIMA. Furthermore, is >> it >>> possible to go from UIMA to OpenNLP ? For example, I am interested in a >>> medical analysis with cTakes, but I cannot find a way how to do it using >>> only the OpenNLP. >>> >>> The reason why I want to rely on OpenNLP as much as possible, is simply >> due >>> to a complexity of applications I am developing, and UIMA would simply >>> complicate everything without a necessity. >>> >>> Thank you kindly for your answers! >>> >>> Damir Olejar >>> >>
