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 <[email protected]> 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
