+1 to start making a release. I would like to be involved too.
R
On 19 Nov 2014 23:40, "Joern Kottmann" wrote:
> Hello,
>
> yes, that should be the current state.
>
> Can you please elaborate on the issue you have.
> Do you get an old version?
>
> We should try to make a release of 1.6.0, I thin
You probably need to include the Apache snapshot repository in
your pom to make that work.
https://repository.apache.org/content/repositories/snapshots/
Maybe we should mention that on our site, so people know how to run
the latest snapshot version.
Jörn
On 11/20/2014 07:52 AM, Rodrigo Agerri
Hi,
Sorry, I was on my mobile.
The issues is that when I add version 1.6.0 as a dependency,
org.apache.opennlp
opennlp-tools
1.6.0-SNAPSHOT
compile
it does not find it. So, either the dependency should be specified
differently or I need to add a repository (an apache repository
pres
The runtime almost scales with the number of cores your
CPU you have. If you have a 4 core CPU you might come down
from 3 hours to 1 hour.
To enabled it you need to train with the -params argument and provide
a config file for the learner. There are samples shipped with OpenNLP.
Jörn
On Wed, 201
Hello,
yes, that should be the current state.
Can you please elaborate on the issue you have.
Do you get an old version?
We should try to make a release of 1.6.0, I think most issues
are already solved and remaining bugs we will uncover during the manual
testing phase.
Jörn
On Wed, 2014-11-19
Hi
Any chance to release snapshot repos to maven central? Or to an apache
snapshots repo?
It would make the use of current trunk via API much easier.
Cheers
Rodrigo
Hi Rodrigo,
No, I am not using multi-threading, it's a simple Java program, took help from
openNLP documentation but it is worth mentioning over here is that as the
corpus is containing 4 million records so my Java program running in eclipse
was frequently giving me java heap space issue (out of
Hi Samik,
Thank you so much for the quick feedback.
1. You can possibly have smaller training sets and see if the models
deteriorate substantially:
Yes I have 4 training sets each containing 1 million records but i dont
understand how it would be useful? because when I am creating a one model out
