added non-pruning intersection and a CRF tagger

- the linear-chain tagger is more of a proof of concept than a real tagger-- the context-free assumptions made in a number of places mean that the algorithms used may not be as efficient as they could be, but the model is as powerful as any CRF
- it would be easy to add latent variables or semi-CRF support (or both!)
- i've added a couple basic features that are often used for POS tagging
- non-pruning intersection is useful for lexical word alignment models and the tagger
- a sample POS tagger model will be committed later

1 files changed, 1 insertions, 0 deletions

diff --git a/training/cluster-ptrain.pl b/training/cluster-ptrain.pl
index 8b06f162..33aab25d 100755
--- a/training/cluster-ptrain.pl
+++ b/training/cluster-ptrain.pl
@@ -36,6 +36,7 @@ GetOptions("cdec=s" => \$DECODER,
            "sigma_squared=f" => \$sigsq,
            "means=s" => \$means_file,
            "optimizer=s" => \$OALG,
+           "gaussian_prior" => \$PRIOR,
            "jobs=i" => \$nodes,
            "pmem=s" => \$pmem
           ) or usage();