diff --git a/moses-chart-cmd/IOWrapper.cpp b/moses-chart-cmd/IOWrapper.cpp
index 401636fa5..571f7e32e 100644
--- a/moses-chart-cmd/IOWrapper.cpp
+++ b/moses-chart-cmd/IOWrapper.cpp
@@ -40,6 +40,7 @@ POSSIBILITY OF SUCH DAMAGE.
 #include "moses/StaticData.h"
 #include "moses/DummyScoreProducers.h"
 #include "moses/InputFileStream.h"
+#include "moses/Incremental.h"
 #include "moses/PhraseDictionary.h"
 #include "moses/ChartTrellisPathList.h"
 #include "moses/ChartTrellisPath.h"
@@ -377,8 +378,136 @@ void IOWrapper::OutputBestHypo(const ChartHypothesis *hypo, long translationId)
   m_singleBestOutputCollector->Write(translationId, out.str());
 }
 
-void IOWrapper::OutputNBestList(const ChartTrellisPathList &nBestList, const ChartHypothesis *bestHypo, const TranslationSystem* system, long translationId)
-{
+void IOWrapper::OutputBestHypo(search::Applied applied, long translationId) {
+  if (!m_singleBestOutputCollector) return;
+  std::ostringstream out;
+  IOWrapper::FixPrecision(out);
+  if (StaticData::Instance().GetOutputHypoScore()) {
+    out << applied.GetScore() << ' ';
+  }
+  Phrase outPhrase;
+  Incremental::ToPhrase(applied, outPhrase);
+  // delete 1st & last
+  CHECK(outPhrase.GetSize() >= 2);
+  outPhrase.RemoveWord(0);
+  outPhrase.RemoveWord(outPhrase.GetSize() - 1);
+  out << outPhrase.GetStringRep(StaticData::Instance().GetOutputFactorOrder());
+  out << '\n';
+  m_singleBestOutputCollector->Write(translationId, out.str());
+}
+
+void IOWrapper::OutputBestNone(long translationId) {
+  if (!m_singleBestOutputCollector) return;
+  if (StaticData::Instance().GetOutputHypoScore()) {
+    m_singleBestOutputCollector->Write(translationId, "0 \n");
+  } else {
+    m_singleBestOutputCollector->Write(translationId, "\n");
+  }
+}
+
+namespace {
+
+void OutputSparseFeatureScores(std::ostream& out, const ScoreComponentCollection &features, const FeatureFunction *ff, std::string &lastName) {
+  const StaticData &staticData = StaticData::Instance();
+  bool labeledOutput = staticData.IsLabeledNBestList();
+  const FVector scores = features.GetVectorForProducer( ff );
+
+  // report weighted aggregate
+  if (! ff->GetSparseFeatureReporting()) {
+  	const FVector &weights = staticData.GetAllWeights().GetScoresVector();
+  	if (labeledOutput && !boost::contains(ff->GetScoreProducerDescription(), ":"))
+  		out << " " << ff->GetScoreProducerWeightShortName() << ":";
+    out << " " << scores.inner_product(weights);
+  }
+
+  // report each feature
+  else {
+  	for(FVector::FNVmap::const_iterator i = scores.cbegin(); i != scores.cend(); i++) {
+  		if (i->second != 0) { // do not report zero-valued features
+  			if (labeledOutput)
+  				out << " " << i->first << ":";
+        out << " " << i->second;
+      }
+    }
+  }
+}
+
+void WriteFeatures(const TranslationSystem &system, const ScoreComponentCollection &features, std::ostream &out) {
+  bool labeledOutput = StaticData::Instance().IsLabeledNBestList();
+  // lm
+  const LMList& lml = system.GetLanguageModels();
+  if (lml.size() > 0) {
+    if (labeledOutput)
+      out << "lm:";
+    LMList::const_iterator lmi = lml.begin();
+    for (; lmi != lml.end(); ++lmi) {
+      out << " " << features.GetScoreForProducer(*lmi);
+    }
+  }
+
+  std::string lastName = "";
+
+  // output stateful sparse features
+  const vector<const StatefulFeatureFunction*>& sff = system.GetStatefulFeatureFunctions();
+  for( size_t i=0; i<sff.size(); i++ )
+    if (sff[i]->GetNumScoreComponents() == ScoreProducer::unlimited)
+      OutputSparseFeatureScores(out, features, sff[i], lastName);
+
+  // translation components
+  const vector<PhraseDictionaryFeature*>& pds = system.GetPhraseDictionaries();
+  if (pds.size() > 0) {
+    for( size_t i=0; i<pds.size(); i++ ) {
+      size_t pd_numinputscore = pds[i]->GetNumInputScores();
+      vector<float> scores = features.GetScoresForProducer( pds[i] );
+      for (size_t j = 0; j<scores.size(); ++j){
+        if (labeledOutput && (i == 0) ){
+          if ((j == 0) || (j == pd_numinputscore)){
+            lastName =  pds[i]->GetScoreProducerWeightShortName(j);
+            out << " " << lastName << ":";
+          }
+        }
+        out << " " << scores[j];
+      }
+    }
+  }
+
+  // word penalty
+  if (labeledOutput)
+    out << " w:";
+  out << " " << features.GetScoreForProducer(system.GetWordPenaltyProducer());
+
+  // generation
+  const vector<GenerationDictionary*>& gds = system.GetGenerationDictionaries();
+  if (gds.size() > 0) {
+    for( size_t i=0; i<gds.size(); i++ ) {
+      size_t pd_numinputscore = gds[i]->GetNumInputScores();
+      vector<float> scores = features.GetScoresForProducer( gds[i] );
+      for (size_t j = 0; j<scores.size(); ++j){
+        if (labeledOutput && (i == 0) ){
+          if ((j == 0) || (j == pd_numinputscore)){
+            lastName =  gds[i]->GetScoreProducerWeightShortName(j);
+            out << " " << lastName << ":";
+          }
+        }
+        out << " " << scores[j];
+      }
+    }
+  }
+
+  // output stateless sparse features
+  lastName = "";
+
+  const vector<const StatelessFeatureFunction*>& slf = system.GetStatelessFeatureFunctions();
+  for( size_t i=0; i<slf.size(); i++ ) {
+    if (slf[i]->GetNumScoreComponents() == ScoreProducer::unlimited) {
+      OutputSparseFeatureScores(out, features, slf[i], lastName);
+    }
+  }
+} 
+
+} // namespace
+
+void IOWrapper::OutputNBestList(const ChartTrellisPathList &nBestList, const TranslationSystem* system, long translationId) {
   std::ostringstream out;
 
   // Check if we're writing to std::cout.
@@ -387,17 +516,10 @@ void IOWrapper::OutputNBestList(const ChartTrellisPathList &nBestList, const Cha
     // preserve existing behaviour, but should probably be done either way.
     IOWrapper::FixPrecision(out);
 
-    // The output from -output-hypo-score is always written to std::cout.
-    if (StaticData::Instance().GetOutputHypoScore()) {
-      if (bestHypo != NULL) {
-        out << bestHypo->GetTotalScore() << " ";
-      } else {
-        out << "0 ";
-      }
-    }
+    // Used to check StaticData's GetOutputHypoScore(), but it makes no sense with nbest output.  
   }
 
-  bool labeledOutput = StaticData::Instance().IsLabeledNBestList();
+  //bool includeAlignment = StaticData::Instance().NBestIncludesAlignment();
   bool includeWordAlignment = StaticData::Instance().PrintAlignmentInfoInNbest();
 
   ChartTrellisPathList::const_iterator iter;
@@ -421,75 +543,7 @@ void IOWrapper::OutputNBestList(const ChartTrellisPathList &nBestList, const Cha
     // before each model type, the corresponding command-line-like name must be emitted
     // MERT script relies on this
 
-    // lm
-    const LMList& lml = system->GetLanguageModels();
-    if (lml.size() > 0) {
-      if (labeledOutput)
-        out << "lm:";
-      LMList::const_iterator lmi = lml.begin();
-      for (; lmi != lml.end(); ++lmi) {
-        out << " " << path.GetScoreBreakdown().GetScoreForProducer(*lmi);
-      }
-    }
-
-    std::string lastName = "";
-
-    // output stateful sparse features
-    const vector<const StatefulFeatureFunction*>& sff = system->GetStatefulFeatureFunctions();
-    for( size_t i=0; i<sff.size(); i++ )
-    	if (sff[i]->GetNumScoreComponents() == ScoreProducer::unlimited)
-    		OutputSparseFeatureScores( out, path, sff[i], lastName );
-
-    // translation components
-    const vector<PhraseDictionaryFeature*>& pds = system->GetPhraseDictionaries();
-    if (pds.size() > 0) {
-      for( size_t i=0; i<pds.size(); i++ ) {
-      	size_t pd_numinputscore = pds[i]->GetNumInputScores();
-      	vector<float> scores = path.GetScoreBreakdown().GetScoresForProducer( pds[i] );
-      	for (size_t j = 0; j<scores.size(); ++j){
-      		if (labeledOutput && (i == 0) ){
-      			if ((j == 0) || (j == pd_numinputscore)){
-      				lastName =  pds[i]->GetScoreProducerWeightShortName(j);
-      				out << " " << lastName << ":";
-      			}
-      		}
-      		out << " " << scores[j];
-      	}
-      }
-    }
-
-    // word penalty
-    if (labeledOutput)
-      out << " w:";
-    out << " " << path.GetScoreBreakdown().GetScoreForProducer(system->GetWordPenaltyProducer());
-
-    // generation
-    const vector<GenerationDictionary*>& gds = system->GetGenerationDictionaries();
-    if (gds.size() > 0) {
-      for( size_t i=0; i<gds.size(); i++ ) {
-      	size_t pd_numinputscore = gds[i]->GetNumInputScores();
-      	vector<float> scores = path.GetScoreBreakdown().GetScoresForProducer( gds[i] );
-      	for (size_t j = 0; j<scores.size(); ++j){
-      		if (labeledOutput && (i == 0) ){
-      			if ((j == 0) || (j == pd_numinputscore)){
-      				lastName =  gds[i]->GetScoreProducerWeightShortName(j);
-      				out << " " << lastName << ":";
-      			}
-      		}
-      		out << " " << scores[j];
-      	}
-      }
-    }
-
-    // output stateless sparse features
-    lastName = "";
-
-    const vector<const StatelessFeatureFunction*>& slf = system->GetStatelessFeatureFunctions();
-    for( size_t i=0; i<slf.size(); i++ ) {
-      if (slf[i]->GetNumScoreComponents() == ScoreProducer::unlimited) {
-        OutputSparseFeatureScores( out, path, slf[i], lastName );
-      }
-    }
+    WriteFeatures(*system, path.GetScoreBreakdown(), out);
 
     // total
     out << " ||| " << path.GetTotalScore();
@@ -524,34 +578,33 @@ void IOWrapper::OutputNBestList(const ChartTrellisPathList &nBestList, const Cha
 
   out <<std::flush;
 
-  CHECK(m_nBestOutputCollector);
+  assert(m_nBestOutputCollector);
   m_nBestOutputCollector->Write(translationId, out.str());
 }
 
-void IOWrapper::OutputSparseFeatureScores( std::ostream& out, const ChartTrellisPath &path, const FeatureFunction *ff, std::string &lastName )
-{
-  const StaticData &staticData = StaticData::Instance();
-  bool labeledOutput = staticData.IsLabeledNBestList();
-  const FVector scores = path.GetScoreBreakdown().GetVectorForProducer( ff );
-
-  // report weighted aggregate
-  if (! ff->GetSparseFeatureReporting()) {
-  	const FVector &weights = staticData.GetAllWeights().GetScoresVector();
-  	if (labeledOutput && !boost::contains(ff->GetScoreProducerDescription(), ":"))
-  		out << " " << ff->GetScoreProducerWeightShortName() << ":";
-    out << " " << scores.inner_product(weights);
+void IOWrapper::OutputNBestList(const std::vector<search::Applied> &nbest, const TranslationSystem &system, long translationId) {
+  std::ostringstream out;
+  // wtf? copied from the original OutputNBestList
+  if (m_nBestOutputCollector->OutputIsCout()) {
+    IOWrapper::FixPrecision(out);
   }
-
-  // report each feature
-  else {
-  	for(FVector::FNVmap::const_iterator i = scores.cbegin(); i != scores.cend(); i++) {
-  		if (i->second != 0) { // do not report zero-valued features
-  			if (labeledOutput)
-  				out << " " << i->first << ":";
-        out << " " << i->second;
-      }
-    }
+  Phrase outputPhrase;
+  ScoreComponentCollection features;
+  for (std::vector<search::Applied>::const_iterator i = nbest.begin(); i != nbest.end(); ++i) {
+    Incremental::PhraseAndFeatures(system, *i, outputPhrase, features);
+    // <s> and </s>
+    CHECK(outputPhrase.GetSize() >= 2);
+    outputPhrase.RemoveWord(0);
+    outputPhrase.RemoveWord(outputPhrase.GetSize() - 1);
+    out << translationId << " ||| ";
+    OutputSurface(out, outputPhrase, m_outputFactorOrder, false);
+    out << " ||| ";
+    WriteFeatures(system, features, out);
+    out << " ||| " << i->GetScore() << '\n';
   }
+  out << std::flush;
+  assert(m_nBestOutputCollector);
+  m_nBestOutputCollector->Write(translationId, out.str());
 }
 
 void IOWrapper::FixPrecision(std::ostream &stream, size_t size)
diff --git a/moses-chart-cmd/IOWrapper.h b/moses-chart-cmd/IOWrapper.h
index dea7355d0..5686d5728 100644
--- a/moses-chart-cmd/IOWrapper.h
+++ b/moses-chart-cmd/IOWrapper.h
@@ -44,6 +44,7 @@ POSSIBILITY OF SUCH DAMAGE.
 #include "moses/OutputCollector.h"
 #include "moses/ChartHypothesis.h"
 #include "moses/ChartTrellisPath.h"
+#include "search/applied.hh"
 
 namespace Moses
 {
@@ -92,14 +93,14 @@ public:
 
   Moses::InputType* GetInput(Moses::InputType *inputType);
   void OutputBestHypo(const Moses::ChartHypothesis *hypo, long translationId);
+  void OutputBestHypo(search::Applied applied, long translationId);
   void OutputBestHypo(const std::vector<const Moses::Factor*>&  mbrBestHypo, long translationId);
-  void OutputNBestList(const Moses::ChartTrellisPathList &nBestList, const Moses::ChartHypothesis *bestHypo, const Moses::TranslationSystem* system, long translationId);
-  void OutputSparseFeatureScores(std::ostream& out, const Moses::ChartTrellisPath &path, const Moses::FeatureFunction *ff, std::string &lastName);
+  void OutputBestNone(long translationId);
+  void OutputNBestList(const Moses::ChartTrellisPathList &nBestList, const Moses::TranslationSystem* system, long translationId);
+  void OutputNBestList(const std::vector<search::Applied> &nbest, const Moses::TranslationSystem &system, long translationId);
   void OutputDetailedTranslationReport(const Moses::ChartHypothesis *hypo, const Moses::Sentence &sentence, long translationId);
   void Backtrack(const Moses::ChartHypothesis *hypo);
 
-  Moses::OutputCollector *ExposeSingleBest() { return m_singleBestOutputCollector; }
-
   void ResetTranslationId();
 
   Moses::OutputCollector *GetSearchGraphOutputCollector() {
diff --git a/moses-chart-cmd/Main.cpp b/moses-chart-cmd/Main.cpp
index ee8099e3f..278783926 100644
--- a/moses-chart-cmd/Main.cpp
+++ b/moses-chart-cmd/Main.cpp
@@ -59,7 +59,7 @@ POSSIBILITY OF SUCH DAMAGE.
 #include "moses/ChartHypothesis.h"
 #include "moses/ChartTrellisPath.h"
 #include "moses/ChartTrellisPathList.h"
-#include "moses/Incremental/Manager.h"
+#include "moses/Incremental.h"
 
 #include "util/usage.hh"
 
@@ -91,10 +91,14 @@ public:
 
     if (staticData.GetSearchAlgorithm() == ChartIncremental) {
       Incremental::Manager manager(*m_source, system);
-      manager.ProcessSentence();
-      if (m_ioWrapper.ExposeSingleBest()) {
-        m_ioWrapper.ExposeSingleBest()->Write(translationId, manager.String() + '\n');
+      const std::vector<search::Applied> &nbest = manager.ProcessSentence();
+      if (!nbest.empty()) {
+        m_ioWrapper.OutputBestHypo(nbest[0], translationId);
+      } else {
+        m_ioWrapper.OutputBestNone(translationId);
       }
+      if (staticData.GetNBestSize() > 0)
+        m_ioWrapper.OutputNBestList(nbest, system, translationId);
       return;
     }
 
@@ -125,7 +129,7 @@ public:
       VERBOSE(2,"WRITING " << nBestSize << " TRANSLATION ALTERNATIVES TO " << staticData.GetNBestFilePath() << endl);
       ChartTrellisPathList nBestList;
       manager.CalcNBest(nBestSize, nBestList,staticData.GetDistinctNBest());
-      m_ioWrapper.OutputNBestList(nBestList, bestHypo, &system, translationId);
+      m_ioWrapper.OutputNBestList(nBestList, &system, translationId);
       IFVERBOSE(2) {
         PrintUserTime("N-Best Hypotheses Generation Time:");
       }
diff --git a/moses/ChartCellLabel.h b/moses/ChartCellLabel.h
index c44462fcc..9fccf71e9 100644
--- a/moses/ChartCellLabel.h
+++ b/moses/ChartCellLabel.h
@@ -23,7 +23,7 @@
 #include "Word.h"
 #include "WordsRange.h"
 
-namespace search { class Vertex; class VertexGenerator; }
+namespace search { class Vertex; }
 
 namespace Moses
 {
@@ -41,7 +41,7 @@ class ChartCellLabel
   union Stack {
     const HypoList *cube; // cube pruning
     const search::Vertex *incr; // incremental search after filling.  
-    search::VertexGenerator *incr_generator; // incremental search during filling.  
+    void *incr_generator; // incremental search during filling.  
   };
 
 
diff --git a/moses/Incremental.cpp b/moses/Incremental.cpp
new file mode 100644
index 000000000..770b0d67e
--- /dev/null
+++ b/moses/Incremental.cpp
@@ -0,0 +1,296 @@
+#include "moses/Incremental.h"
+
+#include "moses/ChartCell.h"
+#include "moses/ChartParserCallback.h"
+#include "moses/FeatureVector.h"
+#include "moses/StaticData.h"
+#include "moses/TranslationSystem.h"
+#include "moses/Util.h"
+
+#include "lm/model.hh"
+#include "search/applied.hh"
+#include "search/config.hh"
+#include "search/context.hh"
+#include "search/edge_generator.hh"
+#include "search/rule.hh"
+#include "search/vertex_generator.hh"
+
+#include <boost/lexical_cast.hpp>
+
+namespace Moses {
+namespace Incremental {
+namespace {
+
+// This is called by EdgeGenerator.  Route hypotheses to separate vertices for
+// each left hand side label, populating ChartCellLabelSet out.  
+template <class Best> class HypothesisCallback {
+  private:
+    typedef search::VertexGenerator<Best> Gen;
+  public:
+    HypothesisCallback(search::ContextBase &context, Best &best, ChartCellLabelSet &out, boost::object_pool<search::Vertex> &vertex_pool)
+      : context_(context), best_(best), out_(out), vertex_pool_(vertex_pool) {}
+
+    void NewHypothesis(search::PartialEdge partial) {
+      // Get the LHS, look it up in the output ChartCellLabel, and upcast it.  
+      // It's not part of the union because it would have been ugly to expose template types in ChartCellLabel.
+      ChartCellLabel::Stack &stack = out_.FindOrInsert(static_cast<const TargetPhrase *>(partial.GetNote().vp)->GetTargetLHS());
+      Gen *entry = static_cast<Gen*>(stack.incr_generator);
+      if (!entry) {
+        entry = generator_pool_.construct(context_, *vertex_pool_.construct(), best_);
+        stack.incr_generator = entry;
+      }
+      entry->NewHypothesis(partial);
+    }
+
+    void FinishedSearch() {
+      for (ChartCellLabelSet::iterator i(out_.mutable_begin()); i != out_.mutable_end(); ++i) {
+        ChartCellLabel::Stack &stack = i->second.MutableStack();
+        Gen *gen = static_cast<Gen*>(stack.incr_generator);
+        gen->FinishedSearch();
+        stack.incr = &gen->Generating();
+      }
+    }
+
+  private:
+    search::ContextBase &context_;
+
+    Best &best_;
+
+    ChartCellLabelSet &out_;
+
+    boost::object_pool<search::Vertex> &vertex_pool_;
+    boost::object_pool<Gen> generator_pool_;
+};
+
+// This is called by the moses parser to collect hypotheses.  It converts to my
+// edges (search::PartialEdge).  
+template <class Model> class Fill : public ChartParserCallback {
+  public:
+    Fill(search::Context<Model> &context, const std::vector<lm::WordIndex> &vocab_mapping, search::Score oov_weight)
+      : context_(context), vocab_mapping_(vocab_mapping), oov_weight_(oov_weight) {}
+
+    void Add(const TargetPhraseCollection &targets, const StackVec &nts, const WordsRange &ignored);
+
+    void AddPhraseOOV(TargetPhrase &phrase, std::list<TargetPhraseCollection*> &waste_memory, const WordsRange &range);
+
+    bool Empty() const { return edges_.Empty(); }
+
+    template <class Best> void Search(Best &best, ChartCellLabelSet &out, boost::object_pool<search::Vertex> &vertex_pool) {
+      HypothesisCallback<Best> callback(context_, best, out, vertex_pool);
+      edges_.Search(context_, callback);
+    }
+
+    // Root: everything into one vertex.  
+    template <class Best> search::History RootSearch(Best &best) {
+      search::Vertex vertex;
+      search::RootVertexGenerator<Best> gen(vertex, best);
+      edges_.Search(context_, gen);
+      return vertex.BestChild();
+    }
+
+  private:
+    lm::WordIndex Convert(const Word &word) const;
+
+    search::Context<Model> &context_;
+
+    const std::vector<lm::WordIndex> &vocab_mapping_;
+
+    search::EdgeGenerator edges_;
+
+    const search::Score oov_weight_;
+};
+
+template <class Model> void Fill<Model>::Add(const TargetPhraseCollection &targets, const StackVec &nts, const WordsRange &) {
+  std::vector<search::PartialVertex> vertices;
+  vertices.reserve(nts.size());
+  float below_score = 0.0;
+  for (StackVec::const_iterator i(nts.begin()); i != nts.end(); ++i) {
+    vertices.push_back((*i)->GetStack().incr->RootPartial());
+    if (vertices.back().Empty()) return;
+    below_score += vertices.back().Bound();
+  }
+
+  std::vector<lm::WordIndex> words;
+  for (TargetPhraseCollection::const_iterator p(targets.begin()); p != targets.end(); ++p) {
+    words.clear();
+    const TargetPhrase &phrase = **p;
+    const AlignmentInfo::NonTermIndexMap &align = phrase.GetAlignNonTerm().GetNonTermIndexMap();
+    search::PartialEdge edge(edges_.AllocateEdge(nts.size()));
+
+    search::PartialVertex *nt = edge.NT();
+    for (size_t i = 0; i < phrase.GetSize(); ++i) {
+      const Word &word = phrase.GetWord(i);
+      if (word.IsNonTerminal()) {
+        *(nt++) = vertices[align[i]];
+        words.push_back(search::kNonTerminal);
+      } else {
+        words.push_back(Convert(word));
+      }
+    }
+
+    edge.SetScore(phrase.GetFutureScore() + below_score);
+    // prob and oov were already accounted for.  
+    search::ScoreRule(context_.LanguageModel(), words, edge.Between());
+
+    search::Note note;
+    note.vp = &phrase;
+    edge.SetNote(note);
+
+    edges_.AddEdge(edge);
+  }
+}
+
+template <class Model> void Fill<Model>::AddPhraseOOV(TargetPhrase &phrase, std::list<TargetPhraseCollection*> &, const WordsRange &) {
+  std::vector<lm::WordIndex> words;
+  CHECK(phrase.GetSize() <= 1);
+  if (phrase.GetSize())
+    words.push_back(Convert(phrase.GetWord(0)));
+
+  search::PartialEdge edge(edges_.AllocateEdge(0));
+  // Appears to be a bug that FutureScore does not already include language model. 
+  search::ScoreRuleRet scored(search::ScoreRule(context_.LanguageModel(), words, edge.Between()));
+  edge.SetScore(phrase.GetFutureScore() + scored.prob * context_.LMWeight() + static_cast<search::Score>(scored.oov) * oov_weight_);
+
+  search::Note note;
+  note.vp = &phrase;
+  edge.SetNote(note);
+
+  edges_.AddEdge(edge);
+}
+
+// TODO: factors (but chart doesn't seem to support factors anyway). 
+template <class Model> lm::WordIndex Fill<Model>::Convert(const Word &word) const {
+  std::size_t factor = word.GetFactor(0)->GetId();
+  return (factor >= vocab_mapping_.size() ? 0 : vocab_mapping_[factor]);
+}
+
+struct ChartCellBaseFactory {
+  ChartCellBase *operator()(size_t startPos, size_t endPos) const {
+    return new ChartCellBase(startPos, endPos);
+  }
+};
+
+} // namespace
+
+Manager::Manager(const InputType &source, const TranslationSystem &system) :
+  source_(source),
+  system_(system),
+  cells_(source, ChartCellBaseFactory()),
+  parser_(source, system, cells_),
+  n_best_(search::NBestConfig(StaticData::Instance().GetNBestSize())) {}
+
+Manager::~Manager() {
+  system_.CleanUpAfterSentenceProcessing(source_);
+}
+
+template <class Model, class Best> search::History Manager::PopulateBest(const Model &model, const std::vector<lm::WordIndex> &words, Best &out) {
+  const LanguageModel &abstract = **system_.GetLanguageModels().begin();
+  const float oov_weight = abstract.OOVFeatureEnabled() ? abstract.GetOOVWeight() : 0.0;
+  const StaticData &data = StaticData::Instance();
+  search::Config config(abstract.GetWeight(), data.GetCubePruningPopLimit(), search::NBestConfig(data.GetNBestSize()));
+  search::Context<Model> context(config, model);
+
+  size_t size = source_.GetSize();
+  boost::object_pool<search::Vertex> vertex_pool(std::max<size_t>(size * size / 2, 32));
+  
+  for (size_t width = 1; width < size; ++width) {
+    for (size_t startPos = 0; startPos <= size-width; ++startPos) {
+      WordsRange range(startPos, startPos + width - 1);
+      Fill<Model> filler(context, words, oov_weight);
+      parser_.Create(range, filler);
+      filler.Search(out, cells_.MutableBase(range).MutableTargetLabelSet(), vertex_pool);
+    }
+  }
+
+  WordsRange range(0, size - 1);
+  Fill<Model> filler(context, words, oov_weight);
+  parser_.Create(range, filler);
+  return filler.RootSearch(out);
+}
+
+template <class Model> void Manager::LMCallback(const Model &model, const std::vector<lm::WordIndex> &words) {
+  std::size_t nbest = StaticData::Instance().GetNBestSize();
+  if (nbest <= 1) {
+    search::History ret = PopulateBest(model, words, single_best_);
+    if (ret) {
+      backing_for_single_.resize(1);
+      backing_for_single_[0] = search::Applied(ret);
+    } else {
+      backing_for_single_.clear();
+    }
+    completed_nbest_ = &backing_for_single_;
+  } else {
+    search::History ret = PopulateBest(model, words, n_best_);
+    if (ret) {
+      completed_nbest_ = &n_best_.Extract(ret);
+    } else {
+      backing_for_single_.clear();
+      completed_nbest_ = &backing_for_single_;
+    }
+  }
+}
+
+template void Manager::LMCallback<lm::ngram::ProbingModel>(const lm::ngram::ProbingModel &model, const std::vector<lm::WordIndex> &words);
+template void Manager::LMCallback<lm::ngram::RestProbingModel>(const lm::ngram::RestProbingModel &model, const std::vector<lm::WordIndex> &words);
+template void Manager::LMCallback<lm::ngram::TrieModel>(const lm::ngram::TrieModel &model, const std::vector<lm::WordIndex> &words);
+template void Manager::LMCallback<lm::ngram::QuantTrieModel>(const lm::ngram::QuantTrieModel &model, const std::vector<lm::WordIndex> &words);
+template void Manager::LMCallback<lm::ngram::ArrayTrieModel>(const lm::ngram::ArrayTrieModel &model, const std::vector<lm::WordIndex> &words);
+template void Manager::LMCallback<lm::ngram::QuantArrayTrieModel>(const lm::ngram::QuantArrayTrieModel &model, const std::vector<lm::WordIndex> &words);
+
+const std::vector<search::Applied> &Manager::ProcessSentence() {
+  const LMList &lms = system_.GetLanguageModels();
+  UTIL_THROW_IF(lms.size() != 1, util::Exception, "Incremental search only supports one language model.");
+  (*lms.begin())->IncrementalCallback(*this);
+  return *completed_nbest_;
+}
+
+namespace {
+
+struct NoOp {
+  void operator()(const TargetPhrase &) const {}
+};
+struct AccumScore {
+  AccumScore(ScoreComponentCollection &out) : out_(&out) {}
+  void operator()(const TargetPhrase &phrase) {
+    out_->PlusEquals(phrase.GetScoreBreakdown());
+  }
+  ScoreComponentCollection *out_;
+};
+template <class Action> void AppendToPhrase(const search::Applied final, Phrase &out, Action action) {
+  assert(final.Valid());
+  const TargetPhrase &phrase = *static_cast<const TargetPhrase*>(final.GetNote().vp);
+  action(phrase);
+  const search::Applied *child = final.Children();
+  for (std::size_t i = 0; i < phrase.GetSize(); ++i) {
+    const Word &word = phrase.GetWord(i);
+    if (word.IsNonTerminal()) {
+      AppendToPhrase(*child++, out, action);
+    } else {
+      out.AddWord(word);
+    }
+  }
+}
+
+} // namespace
+
+void ToPhrase(const search::Applied final, Phrase &out) {
+  out.Clear();
+  AppendToPhrase(final, out, NoOp());
+}
+
+void PhraseAndFeatures(const TranslationSystem &system, const search::Applied final, Phrase &phrase, ScoreComponentCollection &features) {
+  phrase.Clear();
+  features.ZeroAll();
+  AppendToPhrase(final, phrase, AccumScore(features));
+
+  // If we made it this far, there is only one language model.  
+  float full, ignored_ngram;
+  std::size_t ignored_oov;
+  const LanguageModel &model = **system.GetLanguageModels().begin();
+  model.CalcScore(phrase, full, ignored_ngram, ignored_oov);
+  // CalcScore transforms, but EvaluateChart doesn't.  
+  features.Assign(&model, UntransformLMScore(full));
+}
+
+} // namespace Incremental
+} // namespace Moses
diff --git a/moses/Incremental.h b/moses/Incremental.h
new file mode 100644
index 000000000..4bfc2dae3
--- /dev/null
+++ b/moses/Incremental.h
@@ -0,0 +1,60 @@
+#pragma once
+
+#include "lm/word_index.hh"
+#include "search/applied.hh"
+#include "search/nbest.hh"
+
+#include "moses/ChartCellCollection.h"
+#include "moses/ChartParser.h"
+
+#include <vector>
+#include <string>
+
+namespace Moses {
+class ScoreComponentCollection;
+class InputType;
+class TranslationSystem;
+namespace Incremental {
+
+class Manager {
+  public:
+    Manager(const InputType &source, const TranslationSystem &system);
+
+    ~Manager();
+
+    template <class Model> void LMCallback(const Model &model, const std::vector<lm::WordIndex> &words);
+    
+    const std::vector<search::Applied> &ProcessSentence();
+
+    // Call to get the same value as ProcessSentence returned.  
+    const std::vector<search::Applied> &Completed() const {
+      return *completed_nbest_;
+    }
+
+  private:
+    template <class Model, class Best> search::History PopulateBest(const Model &model, const std::vector<lm::WordIndex> &words, Best &out);
+
+    const InputType &source_;
+    const TranslationSystem &system_;
+    ChartCellCollectionBase cells_;
+    ChartParser parser_;
+
+    // Only one of single_best_ or n_best_ will be used, but it was easier to do this than a template. 
+    search::SingleBest single_best_;
+    // ProcessSentence returns a reference to a vector.  ProcessSentence
+    // doesn't have one, so this is populated and returned.  
+    std::vector<search::Applied> backing_for_single_;
+
+    search::NBest n_best_;
+    
+    const std::vector<search::Applied> *completed_nbest_;
+};
+
+// Just get the phrase.
+void ToPhrase(const search::Applied final, Phrase &out);
+// Get the phrase and the features.  
+void PhraseAndFeatures(const TranslationSystem &system, const search::Applied final, Phrase &phrase, ScoreComponentCollection &features);
+
+} // namespace Incremental
+} // namespace Moses
+
diff --git a/moses/Incremental/Fill.cpp b/moses/Incremental/Fill.cpp
deleted file mode 100644
index 6f0baba92..000000000
--- a/moses/Incremental/Fill.cpp
+++ /dev/null
@@ -1,143 +0,0 @@
-#include "Fill.h"
-
-#include "moses/ChartCellLabel.h"
-#include "moses/ChartCellLabelSet.h"
-#include "moses/TargetPhraseCollection.h"
-#include "moses/TargetPhrase.h"
-#include "moses/Word.h"
-
-#include "lm/model.hh"
-#include "search/context.hh"
-#include "search/note.hh"
-#include "search/rule.hh"
-#include "search/vertex.hh"
-#include "search/vertex_generator.hh"
-
-#include <math.h>
-
-namespace Moses {
-namespace Incremental {
-
-template <class Model> Fill<Model>::Fill(search::Context<Model> &context, const std::vector<lm::WordIndex> &vocab_mapping) 
-  : context_(context), vocab_mapping_(vocab_mapping) {}
-
-template <class Model> void Fill<Model>::Add(const TargetPhraseCollection &targets, const StackVec &nts, const WordsRange &) {
-  std::vector<search::PartialVertex> vertices;
-  vertices.reserve(nts.size());
-  float below_score = 0.0;
-  for (StackVec::const_iterator i(nts.begin()); i != nts.end(); ++i) {
-    vertices.push_back((*i)->GetStack().incr->RootPartial());
-    if (vertices.back().Empty()) return;
-    below_score += vertices.back().Bound();
-  }
-
-  std::vector<lm::WordIndex> words;
-  for (TargetPhraseCollection::const_iterator p(targets.begin()); p != targets.end(); ++p) {
-    words.clear();
-    const TargetPhrase &phrase = **p;
-    const AlignmentInfo::NonTermIndexMap &align = phrase.GetAlignNonTerm().GetNonTermIndexMap();
-    search::PartialEdge edge(edges_.AllocateEdge(nts.size()));
-
-    size_t i = 0;
-    bool bos = false;
-    search::PartialVertex *nt = edge.NT();
-    if (phrase.GetSize() && !phrase.GetWord(0).IsNonTerminal()) {
-      lm::WordIndex index = Convert(phrase.GetWord(0));
-      if (context_.LanguageModel().GetVocabulary().BeginSentence() == index) {
-        bos = true;
-      } else {
-        words.push_back(index);
-      }
-      i = 1;
-    }
-    for (; i < phrase.GetSize(); ++i) {
-      const Word &word = phrase.GetWord(i);
-      if (word.IsNonTerminal()) {
-        *(nt++) = vertices[align[i]];
-        words.push_back(search::kNonTerminal);
-      } else {
-        words.push_back(Convert(word));
-      }
-    }
-
-    edge.SetScore(phrase.GetFutureScore() + below_score);
-    search::ScoreRule(context_, words, bos, edge.Between());
-
-    search::Note note;
-    note.vp = &phrase;
-    edge.SetNote(note);
-
-    edges_.AddEdge(edge);
-  }
-}
-
-template <class Model> void Fill<Model>::AddPhraseOOV(TargetPhrase &phrase, std::list<TargetPhraseCollection*> &, const WordsRange &) {
-  std::vector<lm::WordIndex> words;
-  CHECK(phrase.GetSize() <= 1);
-  if (phrase.GetSize())
-    words.push_back(Convert(phrase.GetWord(0)));
-
-  search::PartialEdge edge(edges_.AllocateEdge(0));
-  // Appears to be a bug that FutureScore does not already include language model.  
-  edge.SetScore(phrase.GetFutureScore() + search::ScoreRule(context_, words, false, edge.Between()));
-
-  search::Note note;
-  note.vp = &phrase;
-  edge.SetNote(note);
-
-  edges_.AddEdge(edge);
-}
-
-namespace {
-// Route hypotheses to separate vertices for each left hand side label, populating ChartCellLabelSet out.  
-class HypothesisCallback {
-  public:
-    HypothesisCallback(search::ContextBase &context, ChartCellLabelSet &out, boost::object_pool<search::Vertex> &vertex_pool)
-      : context_(context), out_(out), vertex_pool_(vertex_pool) {}
-
-    void NewHypothesis(search::PartialEdge partial) {
-      search::VertexGenerator *&entry = out_.FindOrInsert(static_cast<const TargetPhrase *>(partial.GetNote().vp)->GetTargetLHS()).incr_generator;
-      if (!entry) {
-        entry = generator_pool_.construct(context_, *vertex_pool_.construct());
-      }
-      entry->NewHypothesis(partial);
-    }
-
-    void FinishedSearch() {
-      for (ChartCellLabelSet::iterator i(out_.mutable_begin()); i != out_.mutable_end(); ++i) {
-        ChartCellLabel::Stack &stack = i->second.MutableStack();
-        stack.incr_generator->FinishedSearch();
-        stack.incr = &stack.incr_generator->Generating();
-      }
-    }
-
-  private:
-    search::ContextBase &context_;
-
-    ChartCellLabelSet &out_;
-
-    boost::object_pool<search::Vertex> &vertex_pool_;
-    boost::object_pool<search::VertexGenerator> generator_pool_;
-};
-} // namespace
-
-template <class Model> void Fill<Model>::Search(ChartCellLabelSet &out, boost::object_pool<search::Vertex> &vertex_pool) {
-  HypothesisCallback callback(context_, out, vertex_pool);
-  edges_.Search(context_, callback);
-}
-
-// TODO: factors (but chart doesn't seem to support factors anyway). 
-template <class Model> lm::WordIndex Fill<Model>::Convert(const Word &word) const {
-  std::size_t factor = word.GetFactor(0)->GetId();
-  return (factor >= vocab_mapping_.size() ? 0 : vocab_mapping_[factor]);
-}
-
-template class Fill<lm::ngram::ProbingModel>;
-template class Fill<lm::ngram::RestProbingModel>;
-template class Fill<lm::ngram::TrieModel>;
-template class Fill<lm::ngram::QuantTrieModel>;
-template class Fill<lm::ngram::ArrayTrieModel>;
-template class Fill<lm::ngram::QuantArrayTrieModel>;
-
-} // namespace Incremental
-} // namespace Moses
diff --git a/moses/Incremental/Fill.h b/moses/Incremental/Fill.h
deleted file mode 100644
index 0f4059d09..000000000
--- a/moses/Incremental/Fill.h
+++ /dev/null
@@ -1,54 +0,0 @@
-#pragma once
-
-#include "moses/ChartParserCallback.h"
-#include "moses/StackVec.h"
-
-#include "lm/word_index.hh"
-#include "search/edge_generator.hh"
-
-#include <boost/pool/object_pool.hpp>
-
-#include <list>
-#include <vector>
-
-namespace search {
-template <class Model> class Context;
-class Vertex;
-} // namespace search
-
-namespace Moses {
-class Word;
-class WordsRange;
-class TargetPhraseCollection;
-class WordsRange;
-class ChartCellLabelSet;
-class TargetPhrase;
-
-namespace Incremental {
-
-// Replacement for ChartTranslationOptionList
-// TODO: implement count and score thresholding.  
-template <class Model> class Fill : public ChartParserCallback {
-  public:
-    Fill(search::Context<Model> &context, const std::vector<lm::WordIndex> &vocab_mapping);
-
-    void Add(const TargetPhraseCollection &targets, const StackVec &nts, const WordsRange &ignored);
-
-    void AddPhraseOOV(TargetPhrase &phrase, std::list<TargetPhraseCollection*> &waste_memory, const WordsRange &range);
-
-    bool Empty() const { return edges_.Empty(); }
-
-    void Search(ChartCellLabelSet &out, boost::object_pool<search::Vertex> &vertex_pool);
-    
-  private:
-    lm::WordIndex Convert(const Word &word) const ;
-
-    search::Context<Model> &context_;
-
-    const std::vector<lm::WordIndex> &vocab_mapping_;
-
-    search::EdgeGenerator edges_;
-};
-
-} // namespace Incremental
-} // namespace Moses
diff --git a/moses/Incremental/Manager.cpp b/moses/Incremental/Manager.cpp
deleted file mode 100644
index 7d684540c..000000000
--- a/moses/Incremental/Manager.cpp
+++ /dev/null
@@ -1,122 +0,0 @@
-#include "Manager.h"
-
-#include "Fill.h"
-
-#include "moses/ChartCell.h"
-#include "moses/TranslationSystem.h"
-#include "moses/StaticData.h"
-
-#include "search/context.hh"
-#include "search/config.hh"
-#include "search/weights.hh"
-
-#include <boost/lexical_cast.hpp>
-
-namespace Moses {
-namespace Incremental {
-
-namespace {
-struct ChartCellBaseFactory {
-  ChartCellBase *operator()(size_t startPos, size_t endPos) const {
-    return new ChartCellBase(startPos, endPos);
-  }
-};
-} // namespace
-
-Manager::Manager(const InputType &source, const TranslationSystem &system) :
-  source_(source),
-  system_(system),
-  cells_(source, ChartCellBaseFactory()),
-  parser_(source, system, cells_) {
-
-}
-
-Manager::~Manager() {
-  system_.CleanUpAfterSentenceProcessing(source_);
-}
-
-namespace {
-
-void ConstructString(const search::Final final, std::ostringstream &stream) {
-  assert(final.Valid());
-  const TargetPhrase &phrase = *static_cast<const TargetPhrase*>(final.GetNote().vp);
-  size_t child = 0;
-  for (std::size_t i = 0; i < phrase.GetSize(); ++i) {
-    const Word &word = phrase.GetWord(i);
-    if (word.IsNonTerminal()) {
-      assert(child < final.GetArity());
-      ConstructString(final.Children()[child++], stream);
-    } else {
-      stream << word[0]->GetString() << ' ';
-    }
-  }
-}
-
-void BestString(const ChartCellLabelSet &labels, std::string &out) {
-  search::Final best;
-  for (ChartCellLabelSet::const_iterator i = labels.begin(); i != labels.end(); ++i) {
-    const search::Final child(i->second.GetStack().incr->BestChild());
-    if (child.Valid() && (!best.Valid() || (child.GetScore() > best.GetScore()))) {
-      best = child;
-    }
-  }
-  if (!best.Valid()) {
-    out.clear();
-    return;
-  }
-  std::ostringstream stream;
-  ConstructString(best, stream);
-  out = stream.str();
-  CHECK(out.size() > 9);
-  // <s>
-  out.erase(0, 4);
-  // </s>
-  out.erase(out.size() - 5);
-  // Hack: include model score
-  out += " ||| ";
-  out += boost::lexical_cast<std::string>(best.GetScore());
-}
-
-} // namespace
-
-
-template <class Model> void Manager::LMCallback(const Model &model, const std::vector<lm::WordIndex> &words) {
-  const LanguageModel &abstract = **system_.GetLanguageModels().begin();
-  search::Weights weights(
-      abstract.GetWeight(), 
-      abstract.OOVFeatureEnabled() ? abstract.GetOOVWeight() : 0.0, 
-      system_.GetWeightWordPenalty());
-  search::Config config(weights, StaticData::Instance().GetCubePruningPopLimit());
-  search::Context<Model> context(config, model);
-
-  size_t size = source_.GetSize();
-
-  boost::object_pool<search::Vertex> vertex_pool(std::max<size_t>(size * size / 2, 32));
-
-  for (size_t width = 1; width <= size; ++width) {
-    for (size_t startPos = 0; startPos <= size-width; ++startPos) {
-      size_t endPos = startPos + width - 1;
-      WordsRange range(startPos, endPos);
-      Fill<Model> filler(context, words);
-      parser_.Create(range, filler);
-      filler.Search(cells_.MutableBase(range).MutableTargetLabelSet(), vertex_pool);
-    }
-  }
-  BestString(cells_.GetBase(WordsRange(0, source_.GetSize() - 1)).GetTargetLabelSet(), output_);
-}
-
-template void Manager::LMCallback<lm::ngram::ProbingModel>(const lm::ngram::ProbingModel &model, const std::vector<lm::WordIndex> &words);
-template void Manager::LMCallback<lm::ngram::RestProbingModel>(const lm::ngram::RestProbingModel &model, const std::vector<lm::WordIndex> &words);
-template void Manager::LMCallback<lm::ngram::TrieModel>(const lm::ngram::TrieModel &model, const std::vector<lm::WordIndex> &words);
-template void Manager::LMCallback<lm::ngram::QuantTrieModel>(const lm::ngram::QuantTrieModel &model, const std::vector<lm::WordIndex> &words);
-template void Manager::LMCallback<lm::ngram::ArrayTrieModel>(const lm::ngram::ArrayTrieModel &model, const std::vector<lm::WordIndex> &words);
-template void Manager::LMCallback<lm::ngram::QuantArrayTrieModel>(const lm::ngram::QuantArrayTrieModel &model, const std::vector<lm::WordIndex> &words);
-
-void Manager::ProcessSentence() {
-  const LMList &lms = system_.GetLanguageModels();
-  UTIL_THROW_IF(lms.size() != 1, util::Exception, "Incremental search only supports one language model.");
-  (*lms.begin())->IncrementalCallback(*this);
-}
-
-} // namespace Incremental
-} // namespace Moses
diff --git a/moses/Incremental/Manager.h b/moses/Incremental/Manager.h
deleted file mode 100644
index ac8d76a81..000000000
--- a/moses/Incremental/Manager.h
+++ /dev/null
@@ -1,35 +0,0 @@
-#pragma once
-
-#include "lm/word_index.hh"
-
-#include "moses/ChartCellCollection.h"
-#include "moses/ChartParser.h"
-
-namespace Moses {
-class InputType;
-class TranslationSystem;
-namespace Incremental {
-
-class Manager {
-  public:
-    Manager(const InputType &source, const TranslationSystem &system);
-
-    ~Manager();
-
-    template <class Model> void LMCallback(const Model &model, const std::vector<lm::WordIndex> &words);
-    
-    void ProcessSentence();
-
-    const std::string &String() const { return output_; }
-
-  private:
-    const InputType &source_;
-    const TranslationSystem &system_;
-    ChartCellCollectionBase cells_;
-    ChartParser parser_;
-
-    std::string output_;
-};
-} // namespace Incremental
-} // namespace Moses
-
diff --git a/moses/Jamfile b/moses/Jamfile
index c05a9c6ab..9caa4e788 100644
--- a/moses/Jamfile
+++ b/moses/Jamfile
@@ -32,7 +32,6 @@ lib moses :
   CYKPlusParser/*.cpp
   RuleTable/*.cpp
   fuzzy-match/*.cpp
-  Incremental/*.cpp
 : #exceptions
   ThreadPool.cpp
   SyntacticLanguageModel.cpp
diff --git a/moses/LM/Ken.cpp b/moses/LM/Ken.cpp
index 25e5a00d3..42e517f17 100644
--- a/moses/LM/Ken.cpp
+++ b/moses/LM/Ken.cpp
@@ -38,7 +38,7 @@ Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
 #include "moses/InputFileStream.h"
 #include "moses/StaticData.h"
 #include "moses/ChartHypothesis.h"
-#include "moses/Incremental/Manager.h"
+#include "moses/Incremental.h"
 
 #include <boost/shared_ptr.hpp>
 
diff --git a/scripts/training/filter-model-given-input.pl b/scripts/training/filter-model-given-input.pl
index df9c528e0..d994fbcef 100755
--- a/scripts/training/filter-model-given-input.pl
+++ b/scripts/training/filter-model-given-input.pl
@@ -119,7 +119,11 @@ while(<INI>) {
     	  print INI_OUT "2 $source_factor $t $w $new_name.bin$table_flag\n";
         }
         elsif ($binarizer && $phrase_table_impl == 0) {
-    	  print INI_OUT "1 $source_factor $t $w $new_name$table_flag\n";
+          if ($binarizer =~ /processPhraseTableMin/) {
+            print INI_OUT "12 $source_factor $t $w $new_name$table_flag\n";
+          } else {
+    	    print INI_OUT "1 $source_factor $t $w $new_name$table_flag\n";
+          }
         } else {
           $new_name .= ".gz" if $opt_gzip;
     	    print INI_OUT "$phrase_table_impl $source_factor $t $w $new_name$table_flag\n";
@@ -147,7 +151,7 @@ while(<INI>) {
 
     	$file =~ s/^.*\/+([^\/]+)/$1/g;
     	my $new_name = "$dir/$file";
-	$new_name =~ s/\.gz//;
+	    $new_name =~ s/\.gz//;
     	print INI_OUT "$factors $t $w $new_name\n";
     	push @TABLE_NEW_NAME,$new_name;
 
@@ -275,11 +279,16 @@ for(my $i=0;$i<=$#TABLE;$i++) {
         # ... hierarchical translation model
         if ($opt_hierarchical) {
           my $cmd = "$binarizer $new_file $new_file.bin";
-	  print STDERR $cmd."\n";
-	  print STDERR `$cmd`;
+          print STDERR $cmd."\n";
+          print STDERR `$cmd`;
         }
         # ... phrase translation model
-        else { 
+        elsif ($binarizer =~ /processPhraseTableMin/) {
+          #compact phrase table
+          my $cmd = "LC_ALL=C sort -T $dir $new_file > $new_file.sorted; $binarizer -in $new_file.sorted -out $new_file -nscores $TABLE_WEIGHTS[$i]; rm $new_file.sorted";
+          print STDERR $cmd."\n";
+          print STDERR `$cmd`;
+        } else { 
           my $cmd = "cat $new_file | LC_ALL=C sort -T $dir | $binarizer -ttable 0 0 - -nscores $TABLE_WEIGHTS[$i] -out $new_file";
           print STDERR $cmd."\n";
           print STDERR `$cmd`;
@@ -289,8 +298,13 @@ for(my $i=0;$i<=$#TABLE;$i++) {
       else {
         my $lexbin = $binarizer; 
         $lexbin =~ s/PhraseTable/LexicalTable/;
-        $lexbin =~ s/^\s*(\S+)\s.+/$1/; # no options
-        my $cmd = "$lexbin -in $new_file -out $new_file";
+        my $cmd;
+        if ($lexbin =~ /processLexicalTableMin/) {
+          $cmd = "LC_ALL=C sort -T $dir $new_file > $new_file.sorted;  $lexbin -in $new_file.sorted -out $new_file; rm $new_file.sorted";
+        } else {
+          $lexbin =~ s/^\s*(\S+)\s.+/$1/; # no options
+          $cmd = "$lexbin -in $new_file -out $new_file";
+        }
         print STDERR $cmd."\n";
         print STDERR `$cmd`;
       }
diff --git a/search/Jamfile b/search/Jamfile
index c00d23828..f6433e0e3 100644
--- a/search/Jamfile
+++ b/search/Jamfile
@@ -1,5 +1 @@
-fakelib search : weights.cc vertex.cc vertex_generator.cc edge_generator.cc rule.cc ../lm//kenlm ../util//kenutil /top//boost_system : : : <include>.. ;
-
-import testing ;
-
-unit-test weights_test : weights_test.cc search /top//boost_unit_test_framework ;
+fakelib search : edge_generator.cc nbest.cc rule.cc vertex.cc vertex_generator.cc ../lm//kenlm ../util//kenutil /top//boost_system : : : <include>.. ;
diff --git a/search/applied.hh b/search/applied.hh
new file mode 100644
index 000000000..bd659e5c0
--- /dev/null
+++ b/search/applied.hh
@@ -0,0 +1,86 @@
+#ifndef SEARCH_APPLIED__
+#define SEARCH_APPLIED__
+
+#include "search/edge.hh"
+#include "search/header.hh"
+#include "util/pool.hh"
+
+#include <math.h>
+
+namespace search {
+
+// A full hypothesis: a score, arity of the rule, a pointer to the decoder's rule (Note), and pointers to non-terminals that were substituted.  
+template <class Below> class GenericApplied : public Header {
+  public:
+    GenericApplied() {}
+
+    GenericApplied(void *location, PartialEdge partial) 
+      : Header(location) {
+      memcpy(Base(), partial.Base(), kHeaderSize);
+      Below *child_out = Children();
+      const PartialVertex *part = partial.NT();
+      const PartialVertex *const part_end_loop = part + partial.GetArity();
+      for (; part != part_end_loop; ++part, ++child_out)
+        *child_out = Below(part->End());
+    }
+    
+    GenericApplied(void *location, Score score, Arity arity, Note note) : Header(location, arity) {
+      SetScore(score);
+      SetNote(note);
+    }
+
+    explicit GenericApplied(History from) : Header(from) {}
+
+
+    // These are arrays of length GetArity().
+    Below *Children() {
+      return reinterpret_cast<Below*>(After());
+    }
+    const Below *Children() const {
+      return reinterpret_cast<const Below*>(After());
+    }
+
+    static std::size_t Size(Arity arity) {
+      return kHeaderSize + arity * sizeof(const Below);
+    }
+};
+
+// Applied rule that references itself.  
+class Applied : public GenericApplied<Applied> {
+  private:
+    typedef GenericApplied<Applied> P;
+
+  public:
+    Applied() {}
+    Applied(void *location, PartialEdge partial) : P(location, partial) {}
+    Applied(History from) : P(from) {}
+};
+
+// How to build single-best hypotheses.  
+class SingleBest {
+  public:
+    typedef PartialEdge Combine;
+
+    void Add(PartialEdge &existing, PartialEdge add) const {
+      if (!existing.Valid() || existing.GetScore() < add.GetScore())
+        existing = add;
+    }
+
+    NBestComplete Complete(PartialEdge partial) {
+      if (!partial.Valid()) 
+        return NBestComplete(NULL, lm::ngram::ChartState(), -INFINITY);
+      void *place_final = pool_.Allocate(Applied::Size(partial.GetArity()));
+      Applied(place_final, partial);
+      return NBestComplete(
+          place_final,
+          partial.CompletedState(),
+          partial.GetScore());
+    }
+
+  private:
+    util::Pool pool_;
+};
+
+} // namespace search
+
+#endif // SEARCH_APPLIED__
diff --git a/search/config.hh b/search/config.hh
index ef8e2354a..ba18c09e9 100644
--- a/search/config.hh
+++ b/search/config.hh
@@ -1,23 +1,36 @@
 #ifndef SEARCH_CONFIG__
 #define SEARCH_CONFIG__
 
-#include "search/weights.hh"
-#include "util/string_piece.hh"
+#include "search/types.hh"
 
 namespace search {
 
+struct NBestConfig {
+  explicit NBestConfig(unsigned int in_size) {
+    keep = in_size;
+    size = in_size;
+  }
+  
+  unsigned int keep, size;
+};
+
 class Config {
   public:
-    Config(const Weights &weights, unsigned int pop_limit) :
-      weights_(weights), pop_limit_(pop_limit) {}
+    Config(Score lm_weight, unsigned int pop_limit, const NBestConfig &nbest) :
+      lm_weight_(lm_weight), pop_limit_(pop_limit), nbest_(nbest) {}
 
-    const Weights &GetWeights() const { return weights_; }
+    Score LMWeight() const { return lm_weight_; }
 
     unsigned int PopLimit() const { return pop_limit_; }
 
+    const NBestConfig &GetNBest() const { return nbest_; }
+
   private:
-    Weights weights_;
+    Score lm_weight_;
+
     unsigned int pop_limit_;
+
+    NBestConfig nbest_;
 };
 
 } // namespace search
diff --git a/search/context.hh b/search/context.hh
index 62163144f..08f21bbf0 100644
--- a/search/context.hh
+++ b/search/context.hh
@@ -1,30 +1,16 @@
 #ifndef SEARCH_CONTEXT__
 #define SEARCH_CONTEXT__
 
-#include "lm/model.hh"
 #include "search/config.hh"
-#include "search/final.hh"
-#include "search/types.hh"
 #include "search/vertex.hh"
-#include "util/exception.hh"
-#include "util/pool.hh"
 
 #include <boost/pool/object_pool.hpp>
-#include <boost/ptr_container/ptr_vector.hpp>
-
-#include <vector>
 
 namespace search {
 
-class Weights;
-
 class ContextBase {
   public:
-    explicit ContextBase(const Config &config) : pop_limit_(config.PopLimit()), weights_(config.GetWeights()) {}
-
-    util::Pool &FinalPool() {
-      return final_pool_;
-    }
+    explicit ContextBase(const Config &config) : config_(config) {}
 
     VertexNode *NewVertexNode() {
       VertexNode *ret = vertex_node_pool_.construct();
@@ -36,18 +22,16 @@ class ContextBase {
       vertex_node_pool_.destroy(node);
     }
 
-    unsigned int PopLimit() const { return pop_limit_; }
+    unsigned int PopLimit() const { return config_.PopLimit(); }
 
-    const Weights &GetWeights() const { return weights_; }
+    Score LMWeight() const { return config_.LMWeight(); }
+
+    const Config &GetConfig() const { return config_; }
 
   private:
-    util::Pool final_pool_;
-
     boost::object_pool<VertexNode> vertex_node_pool_;
 
-    unsigned int pop_limit_;
-
-    const Weights &weights_;
+    Config config_;
 };
 
 template <class Model> class Context : public ContextBase {
diff --git a/search/edge_generator.cc b/search/edge_generator.cc
index 260159b1f..eacf5de5c 100644
--- a/search/edge_generator.cc
+++ b/search/edge_generator.cc
@@ -1,6 +1,7 @@
 #include "search/edge_generator.hh"
 
 #include "lm/left.hh"
+#include "lm/model.hh"
 #include "lm/partial.hh"
 #include "search/context.hh"
 #include "search/vertex.hh"
@@ -38,7 +39,7 @@ template <class Model> void FastScore(const Context<Model> &context, Arity victi
       *cover = *(cover + 1);
     }
   }
-  update.SetScore(update.GetScore() + adjustment * context.GetWeights().LM());
+  update.SetScore(update.GetScore() + adjustment * context.LMWeight());
 }
 
 } // namespace
diff --git a/search/edge_generator.hh b/search/edge_generator.hh
index 582c78b7b..203942c6f 100644
--- a/search/edge_generator.hh
+++ b/search/edge_generator.hh
@@ -2,7 +2,6 @@
 #define SEARCH_EDGE_GENERATOR__
 
 #include "search/edge.hh"
-#include "search/note.hh"
 #include "search/types.hh"
 
 #include <queue>
diff --git a/search/final.hh b/search/final.hh
deleted file mode 100644
index 50e62cf2e..000000000
--- a/search/final.hh
+++ /dev/null
@@ -1,36 +0,0 @@
-#ifndef SEARCH_FINAL__
-#define SEARCH_FINAL__
-
-#include "search/header.hh"
-#include "util/pool.hh"
-
-namespace search {
-
-// A full hypothesis with pointers to children.
-class Final : public Header {
-  public:
-    Final() {}
-
-    Final(util::Pool &pool, Score score, Arity arity, Note note) 
-      : Header(pool.Allocate(Size(arity)), arity) {
-      SetScore(score);
-      SetNote(note);
-    }
-
-    // These are arrays of length GetArity().
-    Final *Children() {
-      return reinterpret_cast<Final*>(After());
-    }
-    const Final *Children() const {
-      return reinterpret_cast<const Final*>(After());
-    }
-
-  private:
-    static std::size_t Size(Arity arity) {
-      return kHeaderSize + arity * sizeof(const Final);
-    }
-};
-
-} // namespace search
-
-#endif // SEARCH_FINAL__
diff --git a/search/header.hh b/search/header.hh
index 25550dbed..69f0eed04 100644
--- a/search/header.hh
+++ b/search/header.hh
@@ -3,7 +3,6 @@
 
 // Header consisting of Score, Arity, and Note
 
-#include "search/note.hh"
 #include "search/types.hh"
 
 #include <stdint.h>
@@ -24,6 +23,9 @@ class Header {
     bool operator<(const Header &other) const {
       return GetScore() < other.GetScore();
     }
+    bool operator>(const Header &other) const {
+      return GetScore() > other.GetScore();
+    }
 
     Arity GetArity() const {
       return *reinterpret_cast<const Arity*>(base_ + sizeof(Score));
@@ -36,9 +38,14 @@ class Header {
       *reinterpret_cast<Note*>(base_ + sizeof(Score) + sizeof(Arity)) = to;
     }
 
+    uint8_t *Base() { return base_; }
+    const uint8_t *Base() const { return base_; }
+
   protected:
     Header() : base_(NULL) {}
 
+    explicit Header(void *base) : base_(static_cast<uint8_t*>(base)) {}
+
     Header(void *base, Arity arity) : base_(static_cast<uint8_t*>(base)) {
       *reinterpret_cast<Arity*>(base_ + sizeof(Score)) = arity;
     }
diff --git a/search/nbest.cc b/search/nbest.cc
new file mode 100644
index 000000000..ec3322c97
--- /dev/null
+++ b/search/nbest.cc
@@ -0,0 +1,106 @@
+#include "search/nbest.hh"
+
+#include "util/pool.hh"
+
+#include <algorithm>
+#include <functional>
+#include <queue>
+
+#include <assert.h>
+#include <math.h>
+
+namespace search {
+
+NBestList::NBestList(std::vector<PartialEdge> &partials, util::Pool &entry_pool, std::size_t keep) {
+  assert(!partials.empty());
+  std::vector<PartialEdge>::iterator end;
+  if (partials.size() > keep) {
+    end = partials.begin() + keep;
+    std::nth_element(partials.begin(), end, partials.end(), std::greater<PartialEdge>());
+  } else {
+    end = partials.end();
+  }
+  for (std::vector<PartialEdge>::const_iterator i(partials.begin()); i != end; ++i) {
+    queue_.push(QueueEntry(entry_pool.Allocate(QueueEntry::Size(i->GetArity())), *i));
+  }
+}
+
+Score NBestList::TopAfterConstructor() const {
+  assert(revealed_.empty());
+  return queue_.top().GetScore();
+}
+
+const std::vector<Applied> &NBestList::Extract(util::Pool &pool, std::size_t n) {
+  while (revealed_.size() < n && !queue_.empty()) {
+    MoveTop(pool);
+  }
+  return revealed_;
+}
+
+Score NBestList::Visit(util::Pool &pool, std::size_t index) {
+  if (index + 1 < revealed_.size())
+    return revealed_[index + 1].GetScore() - revealed_[index].GetScore();
+  if (queue_.empty()) 
+    return -INFINITY;
+  if (index + 1 == revealed_.size())
+    return queue_.top().GetScore() - revealed_[index].GetScore();
+  assert(index == revealed_.size());
+
+  MoveTop(pool);
+
+  if (queue_.empty()) return -INFINITY;
+  return queue_.top().GetScore() - revealed_[index].GetScore();
+}
+
+Applied NBestList::Get(util::Pool &pool, std::size_t index) {
+  assert(index <= revealed_.size());
+  if (index == revealed_.size()) MoveTop(pool);
+  return revealed_[index];
+}
+
+void NBestList::MoveTop(util::Pool &pool) {
+  assert(!queue_.empty());
+  QueueEntry entry(queue_.top());
+  queue_.pop();
+  RevealedRef *const children_begin = entry.Children();
+  RevealedRef *const children_end = children_begin + entry.GetArity();
+  Score basis = entry.GetScore();
+  for (RevealedRef *child = children_begin; child != children_end; ++child) {
+    Score change = child->in_->Visit(pool, child->index_);
+    if (change != -INFINITY) {
+      assert(change < 0.001);
+      QueueEntry new_entry(pool.Allocate(QueueEntry::Size(entry.GetArity())), basis + change, entry.GetArity(), entry.GetNote());
+      std::copy(children_begin, child, new_entry.Children());
+      RevealedRef *update = new_entry.Children() + (child - children_begin);
+      update->in_ = child->in_;
+      update->index_ = child->index_ + 1;
+      std::copy(child + 1, children_end, update + 1);
+      queue_.push(new_entry);
+    }
+    // Gesmundo, A. and Henderson, J. Faster Cube Pruning, IWSLT 2010.
+    if (child->index_) break;
+  }
+
+  // Convert QueueEntry to Applied.  This leaves some unused memory.  
+  void *overwrite = entry.Children();
+  for (unsigned int i = 0; i < entry.GetArity(); ++i) {
+    RevealedRef from(*(static_cast<const RevealedRef*>(overwrite) + i));
+    *(static_cast<Applied*>(overwrite) + i) = from.in_->Get(pool, from.index_);
+  }
+  revealed_.push_back(Applied(entry.Base()));
+}
+
+NBestComplete NBest::Complete(std::vector<PartialEdge> &partials) {
+  assert(!partials.empty());
+  NBestList *list = list_pool_.construct(partials, entry_pool_, config_.keep);
+  return NBestComplete(
+      list,
+      partials.front().CompletedState(), // All partials have the same state
+      list->TopAfterConstructor());
+}
+
+const std::vector<Applied> &NBest::Extract(History history) {
+  return static_cast<NBestList*>(history)->Extract(entry_pool_, config_.size);
+}
+
+} // namespace search
diff --git a/search/nbest.hh b/search/nbest.hh
new file mode 100644
index 000000000..cb7651bc2
--- /dev/null
+++ b/search/nbest.hh
@@ -0,0 +1,81 @@
+#ifndef SEARCH_NBEST__
+#define SEARCH_NBEST__
+
+#include "search/applied.hh"
+#include "search/config.hh"
+#include "search/edge.hh"
+
+#include <boost/pool/object_pool.hpp>
+
+#include <cstddef>
+#include <queue>
+#include <vector>
+
+#include <assert.h>
+
+namespace search {
+
+class NBestList;
+
+class NBestList {
+  private:
+    class RevealedRef {
+      public: 
+        explicit RevealedRef(History history) 
+          : in_(static_cast<NBestList*>(history)), index_(0) {}
+
+      private:
+        friend class NBestList;
+
+        NBestList *in_;
+        std::size_t index_;
+    };
+    
+    typedef GenericApplied<RevealedRef> QueueEntry;
+
+  public:
+    NBestList(std::vector<PartialEdge> &existing, util::Pool &entry_pool, std::size_t keep);
+
+    Score TopAfterConstructor() const;
+
+    const std::vector<Applied> &Extract(util::Pool &pool, std::size_t n);
+
+  private:
+    Score Visit(util::Pool &pool, std::size_t index);
+
+    Applied Get(util::Pool &pool, std::size_t index);
+
+    void MoveTop(util::Pool &pool);
+
+    typedef std::vector<Applied> Revealed;
+    Revealed revealed_;
+
+    typedef std::priority_queue<QueueEntry> Queue;
+    Queue queue_;
+};
+
+class NBest {
+  public:
+    typedef std::vector<PartialEdge> Combine;
+
+    explicit NBest(const NBestConfig &config) : config_(config) {}
+
+    void Add(std::vector<PartialEdge> &existing, PartialEdge addition) const {
+      existing.push_back(addition);
+    }
+
+    NBestComplete Complete(std::vector<PartialEdge> &partials);
+
+    const std::vector<Applied> &Extract(History root);
+
+  private:
+    const NBestConfig config_;
+
+    boost::object_pool<NBestList> list_pool_;
+
+    util::Pool entry_pool_;
+};
+
+} // namespace search
+
+#endif // SEARCH_NBEST__
diff --git a/search/note.hh b/search/note.hh
deleted file mode 100644
index 50bed06ec..000000000
--- a/search/note.hh
+++ /dev/null
@@ -1,12 +0,0 @@
-#ifndef SEARCH_NOTE__
-#define SEARCH_NOTE__
-
-namespace search {
-
-union Note {
-  const void *vp;
-};
-
-} // namespace search
-
-#endif // SEARCH_NOTE__
diff --git a/search/rule.cc b/search/rule.cc
index 5b00207ef..0244a09f7 100644
--- a/search/rule.cc
+++ b/search/rule.cc
@@ -1,7 +1,7 @@
 #include "search/rule.hh"
 
+#include "lm/model.hh"
 #include "search/context.hh"
-#include "search/final.hh"
 
 #include <ostream>
 
@@ -9,35 +9,35 @@
 
 namespace search {
 
-template <class Model> float ScoreRule(const Context<Model> &context, const std::vector<lm::WordIndex> &words, bool prepend_bos, lm::ngram::ChartState *writing) {
-  unsigned int oov_count = 0;
-  float prob = 0.0;
-  const Model &model = context.LanguageModel();
-  const lm::WordIndex oov = model.GetVocabulary().NotFound();
-  for (std::vector<lm::WordIndex>::const_iterator word = words.begin(); ; ++word) {
-    lm::ngram::RuleScore<Model> scorer(model, *(writing++));
-    // TODO: optimize
-    if (prepend_bos && (word == words.begin())) {
-      scorer.BeginSentence();
-    }
-    for (; ; ++word) {
-      if (word == words.end()) {
-        prob += scorer.Finish();
-        return static_cast<float>(oov_count) * context.GetWeights().OOV() + prob * context.GetWeights().LM();
-      }
-      if (*word == kNonTerminal) break;
-      if (*word == oov) ++oov_count;
+template <class Model> ScoreRuleRet ScoreRule(const Model &model, const std::vector<lm::WordIndex> &words, lm::ngram::ChartState *writing) {
+  ScoreRuleRet ret;
+  ret.prob = 0.0;
+  ret.oov = 0;
+  const lm::WordIndex oov = model.GetVocabulary().NotFound(), bos = model.GetVocabulary().BeginSentence();
+  lm::ngram::RuleScore<Model> scorer(model, *(writing++));
+  std::vector<lm::WordIndex>::const_iterator word = words.begin();
+  if (word != words.end() && *word == bos) {
+    scorer.BeginSentence();
+    ++word;
+  }
+  for (; word != words.end(); ++word) {
+    if (*word == kNonTerminal) {
+      ret.prob += scorer.Finish();
+      scorer.Reset(*(writing++));
+    } else {
+      if (*word == oov) ++ret.oov;
       scorer.Terminal(*word);
     }
-    prob += scorer.Finish();
   }
+  ret.prob += scorer.Finish();
+  return ret;
 }
 
-template float ScoreRule(const Context<lm::ngram::RestProbingModel> &model, const std::vector<lm::WordIndex> &words, bool prepend_bos, lm::ngram::ChartState *writing);
-template float ScoreRule(const Context<lm::ngram::ProbingModel> &model, const std::vector<lm::WordIndex> &words, bool prepend_bos, lm::ngram::ChartState *writing);
-template float ScoreRule(const Context<lm::ngram::TrieModel> &model, const std::vector<lm::WordIndex> &words, bool prepend_bos, lm::ngram::ChartState *writing);
-template float ScoreRule(const Context<lm::ngram::QuantTrieModel> &model, const std::vector<lm::WordIndex> &words, bool prepend_bos, lm::ngram::ChartState *writing);
-template float ScoreRule(const Context<lm::ngram::ArrayTrieModel> &model, const std::vector<lm::WordIndex> &words, bool prepend_bos, lm::ngram::ChartState *writing);
-template float ScoreRule(const Context<lm::ngram::QuantArrayTrieModel> &model, const std::vector<lm::WordIndex> &words, bool prepend_bos, lm::ngram::ChartState *writing);
+template ScoreRuleRet ScoreRule(const lm::ngram::RestProbingModel &model, const std::vector<lm::WordIndex> &words, lm::ngram::ChartState *writing);
+template ScoreRuleRet ScoreRule(const lm::ngram::ProbingModel &model, const std::vector<lm::WordIndex> &words, lm::ngram::ChartState *writing);
+template ScoreRuleRet ScoreRule(const lm::ngram::TrieModel &model, const std::vector<lm::WordIndex> &words, lm::ngram::ChartState *writing);
+template ScoreRuleRet ScoreRule(const lm::ngram::QuantTrieModel &model, const std::vector<lm::WordIndex> &words, lm::ngram::ChartState *writing);
+template ScoreRuleRet ScoreRule(const lm::ngram::ArrayTrieModel &model, const std::vector<lm::WordIndex> &words, lm::ngram::ChartState *writing);
+template ScoreRuleRet ScoreRule(const lm::ngram::QuantArrayTrieModel &model, const std::vector<lm::WordIndex> &words, lm::ngram::ChartState *writing);
 
 } // namespace search
diff --git a/search/rule.hh b/search/rule.hh
index 0ce2794db..43ca61625 100644
--- a/search/rule.hh
+++ b/search/rule.hh
@@ -9,11 +9,16 @@
 
 namespace search {
 
-template <class Model> class Context;
-
 const lm::WordIndex kNonTerminal = lm::kMaxWordIndex;
 
-template <class Model> float ScoreRule(const Context<Model> &context, const std::vector<lm::WordIndex> &words, bool prepend_bos, lm::ngram::ChartState *state_out);
+struct ScoreRuleRet {
+  Score prob;
+  unsigned int oov;
+};
+
+// Pass <s> and </s> normally.  
+// Indicate non-terminals with kNonTerminal.  
+template <class Model> ScoreRuleRet ScoreRule(const Model &model, const std::vector<lm::WordIndex> &words, lm::ngram::ChartState *state_out);
 
 } // namespace search
 
diff --git a/search/types.hh b/search/types.hh
index 06eb5bfa2..f9c849b3f 100644
--- a/search/types.hh
+++ b/search/types.hh
@@ -3,12 +3,29 @@
 
 #include <stdint.h>
 
+namespace lm { namespace ngram { class ChartState; } }
+
 namespace search {
 
 typedef float Score;
 
 typedef uint32_t Arity;
 
+union Note {
+  const void *vp;
+};
+
+typedef void *History;
+
+struct NBestComplete {
+  NBestComplete(History in_history, const lm::ngram::ChartState &in_state, Score in_score) 
+    : history(in_history), state(&in_state), score(in_score) {}
+
+  History history;
+  const lm::ngram::ChartState *state;
+  Score score;
+};
+
 } // namespace search
 
 #endif // SEARCH_TYPES__
diff --git a/search/vertex.cc b/search/vertex.cc
index 11f4631fa..45842982c 100644
--- a/search/vertex.cc
+++ b/search/vertex.cc
@@ -19,21 +19,34 @@ struct GreaterByBound : public std::binary_function<const VertexNode *, const Ve
 
 } // namespace
 
-void VertexNode::SortAndSet(ContextBase &context, VertexNode **parent_ptr) {
+void VertexNode::RecursiveSortAndSet(ContextBase &context, VertexNode *&parent_ptr) {
   if (Complete()) {
-    assert(end_.Valid());
+    assert(end_);
     assert(extend_.empty());
-    bound_ = end_.GetScore();
     return;
   }
-  if (extend_.size() == 1 && parent_ptr) {
-    *parent_ptr = extend_[0];
-    extend_[0]->SortAndSet(context, parent_ptr);
+  if (extend_.size() == 1) {
+    parent_ptr = extend_[0];
+    extend_[0]->RecursiveSortAndSet(context, parent_ptr);
     context.DeleteVertexNode(this);
     return;
   }
   for (std::vector<VertexNode*>::iterator i = extend_.begin(); i != extend_.end(); ++i) {
-    (*i)->SortAndSet(context, &*i);
+    (*i)->RecursiveSortAndSet(context, *i);
+  }
+  std::sort(extend_.begin(), extend_.end(), GreaterByBound());
+  bound_ = extend_.front()->Bound();
+}
+
+void VertexNode::SortAndSet(ContextBase &context) {
+  // This is the root.  The root might be empty.  
+  if (extend_.empty()) {
+    bound_ = -INFINITY;
+    return;
+  }
+  // The root cannot be replaced.  There's always one transition.  
+  for (std::vector<VertexNode*>::iterator i = extend_.begin(); i != extend_.end(); ++i) {
+    (*i)->RecursiveSortAndSet(context, *i);
   }
   std::sort(extend_.begin(), extend_.end(), GreaterByBound());
   bound_ = extend_.front()->Bound();
diff --git a/search/vertex.hh b/search/vertex.hh
index 52bc1dfe7..10b3339b9 100644
--- a/search/vertex.hh
+++ b/search/vertex.hh
@@ -2,7 +2,6 @@
 #define SEARCH_VERTEX__
 
 #include "lm/left.hh"
-#include "search/final.hh"
 #include "search/types.hh"
 
 #include <boost/unordered_set.hpp>
@@ -10,6 +9,7 @@
 #include <queue>
 #include <vector>
 
+#include <math.h>
 #include <stdint.h>
 
 namespace search {
@@ -18,7 +18,7 @@ class ContextBase;
 
 class VertexNode {
   public:
-    VertexNode() {}
+    VertexNode() : end_() {}
 
     void InitRoot() {
       extend_.clear();
@@ -26,7 +26,7 @@ class VertexNode {
       state_.left.length = 0;
       state_.right.length = 0;
       right_full_ = false;
-      end_ = Final();
+      end_ = History();
     }
 
     lm::ngram::ChartState &MutableState() { return state_; }
@@ -36,20 +36,21 @@ class VertexNode {
       extend_.push_back(next);
     }
 
-    void SetEnd(Final end) {
-      assert(!end_.Valid());
+    void SetEnd(History end, Score score) {
+      assert(!end_);
       end_ = end;
+      bound_ = score;
     }
     
-    void SortAndSet(ContextBase &context, VertexNode **parent_pointer);
+    void SortAndSet(ContextBase &context);
 
     // Should only happen to a root node when the entire vertex is empty.   
     bool Empty() const {
-      return !end_.Valid() && extend_.empty();
+      return !end_ && extend_.empty();
     }
 
     bool Complete() const {
-      return end_.Valid();
+      return end_;
     }
 
     const lm::ngram::ChartState &State() const { return state_; }
@@ -64,7 +65,7 @@ class VertexNode {
     }
 
     // Will be invalid unless this is a leaf.   
-    const Final End() const { return end_; }
+    const History End() const { return end_; }
 
     const VertexNode &operator[](size_t index) const {
       return *extend_[index];
@@ -75,13 +76,15 @@ class VertexNode {
     }
 
   private:
+    void RecursiveSortAndSet(ContextBase &context, VertexNode *&parent);
+
     std::vector<VertexNode*> extend_;
 
     lm::ngram::ChartState state_;
     bool right_full_;
 
     Score bound_;
-    Final end_;
+    History end_;
 };
 
 class PartialVertex {
@@ -97,7 +100,7 @@ class PartialVertex {
     const lm::ngram::ChartState &State() const { return back_->State(); }
     bool RightFull() const { return back_->RightFull(); }
 
-    Score Bound() const { return Complete() ? back_->End().GetScore() : (*back_)[index_].Bound(); }
+    Score Bound() const { return Complete() ? back_->Bound() : (*back_)[index_].Bound(); }
 
     unsigned char Length() const { return back_->Length(); }
 
@@ -121,7 +124,7 @@ class PartialVertex {
       return ret;
     }
 
-    const Final End() const {
+    const History End() const {
       return back_->End();
     }
 
@@ -130,16 +133,18 @@ class PartialVertex {
     unsigned int index_;
 };
 
+template <class Output> class VertexGenerator;
+
 class Vertex {
   public:
     Vertex() {}
 
     PartialVertex RootPartial() const { return PartialVertex(root_); }
 
-    const Final BestChild() const {
+    const History BestChild() const {
       PartialVertex top(RootPartial());
       if (top.Empty()) {
-        return Final();
+        return History();
       } else {
         PartialVertex continuation;
         while (!top.Complete()) {
@@ -150,8 +155,8 @@ class Vertex {
     }
 
   private:
-    friend class VertexGenerator;
-
+    template <class Output> friend class VertexGenerator;
+    template <class Output> friend class RootVertexGenerator;
     VertexNode root_;
 };
 
diff --git a/search/vertex_generator.cc b/search/vertex_generator.cc
index e18010c38..73139ffc5 100644
--- a/search/vertex_generator.cc
+++ b/search/vertex_generator.cc
@@ -11,23 +11,11 @@
 
 namespace search {
 
-VertexGenerator::VertexGenerator(ContextBase &context, Vertex &gen) : context_(context), gen_(gen) {
-  gen.root_.InitRoot();
-}
-
 #if BOOST_VERSION > 104200
 namespace {
 
 const uint64_t kCompleteAdd = static_cast<uint64_t>(-1);
 
-// Parallel structure to VertexNode.  
-struct Trie {
-  Trie() : under(NULL) {}
-
-  VertexNode *under;
-  boost::unordered_map<uint64_t, Trie> extend;
-};
-
 Trie &FindOrInsert(ContextBase &context, Trie &node, uint64_t added, const lm::ngram::ChartState &state, unsigned char left, bool left_full, unsigned char right, bool right_full) {
   Trie &next = node.extend[added];
   if (!next.under) {
@@ -43,19 +31,10 @@ Trie &FindOrInsert(ContextBase &context, Trie &node, uint64_t added, const lm::n
   return next;
 }
 
-void CompleteTransition(ContextBase &context, Trie &starter, PartialEdge partial) {
-  Final final(context.FinalPool(), partial.GetScore(), partial.GetArity(), partial.GetNote());
-  Final *child_out = final.Children();
-  const PartialVertex *part = partial.NT();
-  const PartialVertex *const part_end_loop = part + partial.GetArity();
-  for (; part != part_end_loop; ++part, ++child_out)
-    *child_out = part->End();
+} // namespace
 
-  starter.under->SetEnd(final);
-}
-
-void AddHypothesis(ContextBase &context, Trie &root, PartialEdge partial) {
-  const lm::ngram::ChartState &state = partial.CompletedState();
+void AddHypothesis(ContextBase &context, Trie &root, const NBestComplete &end) {
+  const lm::ngram::ChartState &state = *end.state;
   
   unsigned char left = 0, right = 0;
   Trie *node = &root;
@@ -81,30 +60,9 @@ void AddHypothesis(ContextBase &context, Trie &root, PartialEdge partial) {
   }
 
   node = &FindOrInsert(context, *node, kCompleteAdd - state.left.full, state, state.left.length, true, state.right.length, true);
-  CompleteTransition(context, *node, partial);
-}
-
-} // namespace
-
-#else // BOOST_VERSION
-
-struct Trie {
-  VertexNode *under;
-};
-
-void AddHypothesis(ContextBase &context, Trie &root, PartialEdge partial) {
-  UTIL_THROW(util::Exception, "Upgrade Boost to >= 1.42.0 to use incremental search.");
+  node->under->SetEnd(end.history, end.score);
 }
 
 #endif // BOOST_VERSION
 
-void VertexGenerator::FinishedSearch() {
-  Trie root;
-  root.under = &gen_.root_;
-  for (Existing::const_iterator i(existing_.begin()); i != existing_.end(); ++i) {
-    AddHypothesis(context_, root, i->second);
-  }
-  root.under->SortAndSet(context_, NULL);
-}
-
 } // namespace search
diff --git a/search/vertex_generator.hh b/search/vertex_generator.hh
index 60e86112a..da563c2df 100644
--- a/search/vertex_generator.hh
+++ b/search/vertex_generator.hh
@@ -2,9 +2,11 @@
 #define SEARCH_VERTEX_GENERATOR__
 
 #include "search/edge.hh"
+#include "search/types.hh"
 #include "search/vertex.hh"
 
 #include <boost/unordered_map.hpp>
+#include <boost/version.hpp>
 
 namespace lm {
 namespace ngram {
@@ -15,21 +17,44 @@ class ChartState;
 namespace search {
 
 class ContextBase;
-class Final;
 
-class VertexGenerator {
+#if BOOST_VERSION > 104200
+// Parallel structure to VertexNode.  
+struct Trie {
+  Trie() : under(NULL) {}
+
+  VertexNode *under;
+  boost::unordered_map<uint64_t, Trie> extend;
+};
+
+void AddHypothesis(ContextBase &context, Trie &root, const NBestComplete &end);
+
+#endif // BOOST_VERSION
+
+// Output makes the single-best or n-best list.   
+template <class Output> class VertexGenerator {
   public:
-    VertexGenerator(ContextBase &context, Vertex &gen);
-
-    void NewHypothesis(PartialEdge partial) {
-      const lm::ngram::ChartState &state = partial.CompletedState();
-      std::pair<Existing::iterator, bool> ret(existing_.insert(std::make_pair(hash_value(state), partial)));
-      if (!ret.second && ret.first->second < partial) {
-        ret.first->second = partial;
-      }
+    VertexGenerator(ContextBase &context, Vertex &gen, Output &nbest) : context_(context), gen_(gen), nbest_(nbest) {
+      gen.root_.InitRoot();
     }
 
-    void FinishedSearch();
+    void NewHypothesis(PartialEdge partial) {
+      nbest_.Add(existing_[hash_value(partial.CompletedState())], partial);
+    }
+
+    void FinishedSearch() {
+#if BOOST_VERSION > 104200
+      Trie root;
+      root.under = &gen_.root_;
+      for (typename Existing::iterator i(existing_.begin()); i != existing_.end(); ++i) {
+        AddHypothesis(context_, root, nbest_.Complete(i->second));
+      }
+      existing_.clear();
+      root.under->SortAndSet(context_);
+#else
+      UTIL_THROW(util::Exception, "Upgrade Boost to >= 1.42.0 to use incremental search.");
+#endif
+    }
 
     const Vertex &Generating() const { return gen_; }
 
@@ -38,8 +63,35 @@ class VertexGenerator {
 
     Vertex &gen_;
 
-    typedef boost::unordered_map<uint64_t, PartialEdge> Existing;
+    typedef boost::unordered_map<uint64_t, typename Output::Combine> Existing;
     Existing existing_;
+
+    Output &nbest_;
+};
+
+// Special case for root vertex: everything should come together into the root
+// node.  In theory, this should happen naturally due to state collapsing with
+// <s> and </s>.  If that's the case, VertexGenerator is fine, though it will
+// make one connection.  
+template <class Output> class RootVertexGenerator {
+  public:
+    RootVertexGenerator(Vertex &gen, Output &out) : gen_(gen), out_(out) {}
+
+    void NewHypothesis(PartialEdge partial) {
+      out_.Add(combine_, partial);
+    }
+
+    void FinishedSearch() {
+      gen_.root_.InitRoot();
+      NBestComplete completed(out_.Complete(combine_));
+      gen_.root_.SetEnd(completed.history, completed.score);
+    }
+
+  private:
+    Vertex &gen_;
+    
+    typename Output::Combine combine_;
+    Output &out_;
 };
 
 } // namespace search
diff --git a/search/weights.cc b/search/weights.cc
deleted file mode 100644
index d65471ad7..000000000
--- a/search/weights.cc
+++ /dev/null
@@ -1,71 +0,0 @@
-#include "search/weights.hh"
-#include "util/tokenize_piece.hh"
-
-#include <cstdlib>
-
-namespace search {
-
-namespace {
-struct Insert {
-  void operator()(boost::unordered_map<std::string, search::Score> &map, StringPiece name, search::Score score) const {
-    std::string copy(name.data(), name.size());
-    map[copy] = score;
-  }
-};
-
-struct DotProduct {
-  search::Score total;
-  DotProduct() : total(0.0) {}
-
-  void operator()(const boost::unordered_map<std::string, search::Score> &map, StringPiece name, search::Score score) {
-    boost::unordered_map<std::string, search::Score>::const_iterator i(FindStringPiece(map, name));
-    if (i != map.end()) 
-      total += score * i->second;
-  }
-};
-
-template <class Map, class Op> void Parse(StringPiece text, Map &map, Op &op) {
-  for (util::TokenIter<util::SingleCharacter, true> spaces(text, ' '); spaces; ++spaces) {
-    util::TokenIter<util::SingleCharacter> equals(*spaces, '=');
-    UTIL_THROW_IF(!equals, WeightParseException, "Bad weight token " << *spaces);
-    StringPiece name(*equals);
-    UTIL_THROW_IF(!++equals, WeightParseException, "Bad weight token " << *spaces);
-    char *end;
-    // Assumes proper termination.  
-    double value = std::strtod(equals->data(), &end);
-    UTIL_THROW_IF(end != equals->data() + equals->size(), WeightParseException, "Failed to parse weight" << *equals);
-    UTIL_THROW_IF(++equals, WeightParseException, "Too many equals in " << *spaces);
-    op(map, name, value);
-  }
-}
-
-} // namespace
-
-Weights::Weights(StringPiece text) {
-  Insert op;
-  Parse<Map, Insert>(text, map_, op);
-  lm_ = Steal("LanguageModel");
-  oov_ = Steal("OOV");
-  word_penalty_ = Steal("WordPenalty");
-}
-
-Weights::Weights(Score lm, Score oov, Score word_penalty) : lm_(lm), oov_(oov), word_penalty_(word_penalty) {}
-
-search::Score Weights::DotNoLM(StringPiece text) const {
-  DotProduct dot;
-  Parse<const Map, DotProduct>(text, map_, dot);
-  return dot.total;
-}
-
-float Weights::Steal(const std::string &str) {
-  Map::iterator i(map_.find(str));
-  if (i == map_.end()) {
-    return 0.0;
-  } else {
-    float ret = i->second;
-    map_.erase(i);
-    return ret;
-  }
-}
-
-} // namespace search
diff --git a/search/weights.hh b/search/weights.hh
deleted file mode 100644
index df1c419f0..000000000
--- a/search/weights.hh
+++ /dev/null
@@ -1,52 +0,0 @@
-// For now, the individual features are not kept.  
-#ifndef SEARCH_WEIGHTS__
-#define SEARCH_WEIGHTS__
-
-#include "search/types.hh"
-#include "util/exception.hh"
-#include "util/string_piece.hh"
-
-#include <boost/unordered_map.hpp>
-
-#include <string>
-
-namespace search {
-
-class WeightParseException : public util::Exception {
-  public:
-    WeightParseException() {}
-    ~WeightParseException() throw() {}
-};
-
-class Weights {
-  public:
-    // Parses weights, sets lm_weight_, removes it from map_.
-    explicit Weights(StringPiece text);
-
-    // Just the three scores we care about adding.   
-    Weights(Score lm, Score oov, Score word_penalty);
-
-    Score DotNoLM(StringPiece text) const;
-
-    Score LM() const { return lm_; }
-
-    Score OOV() const { return oov_; }
-
-    Score WordPenalty() const { return word_penalty_; }
-
-    // Mostly for testing.  
-    const boost::unordered_map<std::string, Score> &GetMap() const { return map_; }
-
-  private:
-    float Steal(const std::string &str);
-
-    typedef boost::unordered_map<std::string, Score> Map;
-
-    Map map_;
-
-    Score lm_, oov_, word_penalty_;
-};
-
-} // namespace search
-
-#endif // SEARCH_WEIGHTS__
diff --git a/search/weights_test.cc b/search/weights_test.cc
deleted file mode 100644
index 4811ff060..000000000
--- a/search/weights_test.cc
+++ /dev/null
@@ -1,38 +0,0 @@
-#include "search/weights.hh"
-
-#define BOOST_TEST_MODULE WeightTest
-#include <boost/test/unit_test.hpp>
-#include <boost/test/floating_point_comparison.hpp>
-
-namespace search {
-namespace {
-
-#define CHECK_WEIGHT(value, string) \
-  i = parsed.find(string); \
-  BOOST_REQUIRE(i != parsed.end()); \
-  BOOST_CHECK_CLOSE((value), i->second, 0.001);
-
-BOOST_AUTO_TEST_CASE(parse) {
-  // These are not real feature weights.  
-  Weights w("rarity=0 phrase-SGT=0 phrase-TGS=9.45117 lhsGrhs=0 lexical-SGT=2.33833 lexical-TGS=-28.3317 abstract?=0 LanguageModel=3 lexical?=1 glue?=5");
-  const boost::unordered_map<std::string, search::Score> &parsed = w.GetMap();
-  boost::unordered_map<std::string, search::Score>::const_iterator i;
-  CHECK_WEIGHT(0.0, "rarity");
-  CHECK_WEIGHT(0.0, "phrase-SGT");
-  CHECK_WEIGHT(9.45117, "phrase-TGS");
-  CHECK_WEIGHT(2.33833, "lexical-SGT");
-  BOOST_CHECK(parsed.end() == parsed.find("lm"));
-  BOOST_CHECK_CLOSE(3.0, w.LM(), 0.001);
-  CHECK_WEIGHT(-28.3317, "lexical-TGS");
-  CHECK_WEIGHT(5.0, "glue?");
-}
-
-BOOST_AUTO_TEST_CASE(dot) {
-  Weights w("rarity=0 phrase-SGT=0 phrase-TGS=9.45117 lhsGrhs=0 lexical-SGT=2.33833 lexical-TGS=-28.3317 abstract?=0 LanguageModel=3 lexical?=1 glue?=5");
-  BOOST_CHECK_CLOSE(9.45117 * 3.0, w.DotNoLM("phrase-TGS=3.0"), 0.001);
-  BOOST_CHECK_CLOSE(9.45117 * 3.0, w.DotNoLM("phrase-TGS=3.0 LanguageModel=10"), 0.001);
-  BOOST_CHECK_CLOSE(9.45117 * 3.0 + 28.3317 * 17.4, w.DotNoLM("rarity=5 phrase-TGS=3.0 LanguageModel=10 lexical-TGS=-17.4"), 0.001);
-}
-
-} // namespace
-} // namespace search