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From Mark G <giaconiam...@gmail.com>
Subject Re: Support for sequence models
Date Mon, 20 Jan 2014 13:55:14 GMT
Sounds like a good change, but I have two questions: will this affect the
current APIs? Will people's maxent models still work if they are using a
Maxent model now in a component that will soon require a Seq tagging model
after the change?


On Mon, Jan 20, 2014 at 8:44 AM, Richard Eckart de Castilho <
richard.eckart@gmail.com> wrote:

> Would it still be possible to use the current 1.5.x models with OpenNLP
> after the change?
>
> -- Richard
>
> On 20.01.2014, at 07:48, Jörn Kottmann <kottmann@gmail.com> wrote:
>
> > Hi all,
> >
> > in OpenNLP we have a couple of components which rely on sequence tagging.
> > Right now they are using a normal classifier and search for a good
> sequence via beam search.
> >
> > I would like to propose that we change that a bit, all components which
> are based on sequence
> > tagging should use a Sequence Classification Model instead of directly
> using an
> > Event Classification Model (currently named MaxentModel).
> >
> > The change will have two advantages, It will be possible to integrate ml
> algorithm which operate on a sequence
> > level (e.g. CRF) and it would be easy to exchange beam search against a
> similar (maybe enhanced) algorithm.
> >
> > On the training side we already have support for training on sequences.
> Anyway the current implementation is a bit
> > unlucky because the sequence training class can only return an Event
> Classification Model. I will change that so that
> > a Sequence Classification Model has to be returned, and the Perceptron
> Sequence Model will be returned as a
> > Sequence Classification Model instead.
> >
> > Any thoughts?
> >
> > Jörn
>

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