opennlp-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Jason Baldridge <>
Subject Re: using Scala for
Date Tue, 10 Jan 2012 05:20:28 GMT
+1 to this in general, though I'm not into over-architecting things
initially. Would be great to get things humming and then start supporting
more pluggability.

On Sat, Jan 7, 2012 at 7:33 AM, Jörn Kottmann <> wrote:

> On 1/7/12 2:22 PM, Grant Ingersoll wrote:
>> Being able to take advantage of other classifiers seems like it would be
>> a really nice thing to be able to do.  I'd love to put OpenNLP over Mahout
>> or others.
>> Besides, for testing purposes, if you could plugin the existing
>> capability versus your new rewrite (in Scala) then you could easily compare
>> the two.  I can't imagine the abstraction layer is more than a few
>> interfaces or abstract classes plus a bit of configuration/injection/fill
>> in the blank that allows one to specify the implementation.
> Yes, we need plug-able classifiers and support for extensive
> modification/extension of
> our existing components. You are welcome to help us with that.
> One way of implementing this is to specify a (optional) factory class
> during training
> which is used to create a model (classifier). A second type of factory
> class could
> be specified to modify a component.
> These factory class names will be stored in our zip model package, and can
> then be used to instantiated the extensions which are necessary to run the
> component.
> The disadvantage of this approach is that it might not work well with OSGi.
> A big advantage is that OpenNLP itself will take care of configuring
> everything
> and the code needed to run an OpenNLP component is identical, even if the
> model
> uses "custom" extensions. These must only be on the class path.
> Jörn

Jason Baldridge
Associate Professor, Department of Linguistics
The University of Texas at Austin

  • Unnamed multipart/alternative (inline, None, 0 bytes)
View raw message