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, 17 insertions, 0 deletions

diff --git a/decoder/tagger.h b/decoder/tagger.h
new file mode 100644
index 00000000..900019f2
--- /dev/null
+++ b/decoder/tagger.h
@@ -0,0 +1,17 @@
+#ifndef _TAGGER_H_
+#define _TAGGER_H_
+
+#include "translator.h"
+
+struct TaggerImpl;
+struct Tagger : public Translator {
+  Tagger(const boost::program_options::variables_map& conf);
+  bool Translate(const std::string& input,
+                 SentenceMetadata* smeta,
+                 const std::vector<double>& weights,
+                 Hypergraph* forest);
+ private:
+  boost::shared_ptr<TaggerImpl> pimpl_;
+};
+
+#endif