Updated incremental, updated kenlm. Incremental assumes <s>

30 files changed, 680 insertions, 405 deletions

diff --git a/decoder/incremental.cc b/decoder/incremental.cc
index 46615b0b..85647a44 100644
--- a/decoder/incremental.cc
+++ b/decoder/incremental.cc
@@ -6,6 +6,7 @@
 
 #include "lm/enumerate_vocab.hh"
 #include "lm/model.hh"
+#include "search/applied.hh"
 #include "search/config.hh"
 #include "search/context.hh"
 #include "search/edge.hh"
@@ -48,16 +49,16 @@ template <class Model> class Incremental : public IncrementalBase {
     Incremental(const char *model_file, const std::vector<weight_t> &weights) :
       IncrementalBase(weights), 
       m_(model_file, GetConfig()),
-      weights_(
-          weights[FD::Convert("KLanguageModel")],
-          weights[FD::Convert("KLanguageModel_OOV")],
-          weights[FD::Convert("WordPenalty")]) {
-      std::cerr << "Weights KLanguageModel " << weights_.LM() << " KLanguageModel_OOV " << weights_.OOV() << " WordPenalty " << weights_.WordPenalty() << std::endl;
+      lm_(weights[FD::Convert("KLanguageModel")]),
+      oov_(weights[FD::Convert("KLanguageModel_OOV")]),
+      word_penalty_(weights[FD::Convert("WordPenalty")]) {
+      std::cerr << "Weights KLanguageModel " << lm_ << " KLanguageModel_OOV " << oov_ << " WordPenalty " << word_penalty_ << std::endl;
     }
+
     void Search(unsigned int pop_limit, const Hypergraph &hg) const;
 
   private:
-    void ConvertEdge(const search::Context<Model> &context, bool final, search::Vertex *vertices, const Hypergraph::Edge &in, search::EdgeGenerator &gen) const;
+    void ConvertEdge(const search::Context<Model> &context, search::Vertex *vertices, const Hypergraph::Edge &in, search::EdgeGenerator &gen) const;
 
     lm::ngram::Config GetConfig() {
       lm::ngram::Config ret;
@@ -69,46 +70,47 @@ template <class Model> class Incremental : public IncrementalBase {
 
     const Model m_;
 
-    const search::Weights weights_;
+    const float lm_, oov_, word_penalty_;
 };
 
-void PrintFinal(const Hypergraph &hg, const search::Final final) {
+void PrintApplied(const Hypergraph &hg, const search::Applied final) {
   const std::vector<WordID> &words = static_cast<const Hypergraph::Edge*>(final.GetNote().vp)->rule_->e();
-  const search::Final *child(final.Children());
+  const search::Applied *child(final.Children());
   for (std::vector<WordID>::const_iterator i = words.begin(); i != words.end(); ++i) {
     if (*i > 0) {
       std::cout << TD::Convert(*i) << ' ';
     } else {
-      PrintFinal(hg, *child++);
+      PrintApplied(hg, *child++);
     }
   }
 }
 
 template <class Model> void Incremental<Model>::Search(unsigned int pop_limit, const Hypergraph &hg) const {
   boost::scoped_array<search::Vertex> out_vertices(new search::Vertex[hg.nodes_.size()]);
-  search::Config config(weights_, pop_limit);
+  search::Config config(lm_, pop_limit, search::NBestConfig(1));
   search::Context<Model> context(config, m_);
+  search::SingleBest best;
 
   for (unsigned int i = 0; i < hg.nodes_.size() - 1; ++i) {
     search::EdgeGenerator gen;
     const Hypergraph::EdgesVector &down_edges = hg.nodes_[i].in_edges_;
     for (unsigned int j = 0; j < down_edges.size(); ++j) {
       unsigned int edge_index = down_edges[j];
-      ConvertEdge(context, i == hg.nodes_.size() - 2, out_vertices.get(), hg.edges_[edge_index], gen);
+      ConvertEdge(context, out_vertices.get(), hg.edges_[edge_index], gen);
     }
-    search::VertexGenerator vertex_gen(context, out_vertices[i]);
+    search::VertexGenerator<search::SingleBest> vertex_gen(context, out_vertices[i], best);
     gen.Search(context, vertex_gen);
   }
-  const search::Final top = out_vertices[hg.nodes_.size() - 2].BestChild();
+  const search::Applied top = out_vertices[hg.nodes_.size() - 2].BestChild();
   if (!top.Valid()) {
     std::cout << "NO PATH FOUND" << std::endl;
   } else {
-    PrintFinal(hg, top);
+    PrintApplied(hg, top);
     std::cout << "||| " << top.GetScore() << std::endl;
   }
 }
 
-template <class Model> void Incremental<Model>::ConvertEdge(const search::Context<Model> &context, bool final, search::Vertex *vertices, const Hypergraph::Edge &in, search::EdgeGenerator &gen) const {
+template <class Model> void Incremental<Model>::ConvertEdge(const search::Context<Model> &context, search::Vertex *vertices, const Hypergraph::Edge &in, search::EdgeGenerator &gen) const {
   const std::vector<WordID> &e = in.rule_->e();
   std::vector<lm::WordIndex> words;
   words.reserve(e.size());
@@ -127,10 +129,6 @@ template <class Model> void Incremental<Model>::ConvertEdge(const search::Contex
     }
   }
 
-  if (final) {
-    words.push_back(m_.GetVocabulary().EndSentence());
-  }
-
   search::PartialEdge out(gen.AllocateEdge(nts.size()));
 
   memcpy(out.NT(), &nts[0], sizeof(search::PartialVertex) * nts.size());
@@ -140,8 +138,10 @@ template <class Model> void Incremental<Model>::ConvertEdge(const search::Contex
   out.SetNote(note);
 
   score += in.rule_->GetFeatureValues().dot(cdec_weights_);
-  score -= static_cast<float>(terminals) * context.GetWeights().WordPenalty() / M_LN10;
-  score += search::ScoreRule(context, words, final, out.Between());
+  score -= static_cast<float>(terminals) * word_penalty_ / M_LN10;
+  search::ScoreRuleRet res(search::ScoreRule(context.LanguageModel(), words, out.Between()));
+  score += res.prob * lm_ + static_cast<float>(res.oov) * oov_;
+
   out.SetScore(score);
 
   gen.AddEdge(out);
diff --git a/klm/lm/left.hh b/klm/lm/left.hh
index 8c27232e..85c1ea37 100644
--- a/klm/lm/left.hh
+++ b/klm/lm/left.hh
@@ -51,36 +51,36 @@ namespace ngram {
 
 template <class M> class RuleScore {
   public:
-    explicit RuleScore(const M &model, ChartState &out) : model_(model), out_(out), left_done_(false), prob_(0.0) {
+    explicit RuleScore(const M &model, ChartState &out) : model_(model), out_(&out), left_done_(false), prob_(0.0) {
       out.left.length = 0;
       out.right.length = 0;
     }
 
     void BeginSentence() {
-      out_.right = model_.BeginSentenceState();
-      // out_.left is empty.
+      out_->right = model_.BeginSentenceState();
+      // out_->left is empty.
       left_done_ = true;
     }
 
     void Terminal(WordIndex word) {
-      State copy(out_.right);
-      FullScoreReturn ret(model_.FullScore(copy, word, out_.right));
+      State copy(out_->right);
+      FullScoreReturn ret(model_.FullScore(copy, word, out_->right));
       if (left_done_) { prob_ += ret.prob; return; }
       if (ret.independent_left) {
         prob_ += ret.prob;
         left_done_ = true;
         return;
       }
-      out_.left.pointers[out_.left.length++] = ret.extend_left;
+      out_->left.pointers[out_->left.length++] = ret.extend_left;
       prob_ += ret.rest;
-      if (out_.right.length != copy.length + 1)
+      if (out_->right.length != copy.length + 1)
         left_done_ = true;
     }
 
     // Faster version of NonTerminal for the case where the rule begins with a non-terminal.  
     void BeginNonTerminal(const ChartState &in, float prob = 0.0) {
       prob_ = prob;
-      out_ = in;
+      *out_ = in;
       left_done_ = in.left.full;
     }
 
@@ -89,23 +89,23 @@ template <class M> class RuleScore {
       
       if (!in.left.length) {
         if (in.left.full) {
-          for (const float *i = out_.right.backoff; i < out_.right.backoff + out_.right.length; ++i) prob_ += *i;
+          for (const float *i = out_->right.backoff; i < out_->right.backoff + out_->right.length; ++i) prob_ += *i;
           left_done_ = true;
-          out_.right = in.right;
+          out_->right = in.right;
         }
         return;
       }
 
-      if (!out_.right.length) {
-        out_.right = in.right;
+      if (!out_->right.length) {
+        out_->right = in.right;
         if (left_done_) {
           prob_ += model_.UnRest(in.left.pointers, in.left.pointers + in.left.length, 1);
           return;
         }
-        if (out_.left.length) {
+        if (out_->left.length) {
           left_done_ = true;
         } else {
-          out_.left = in.left;
+          out_->left = in.left;
           left_done_ = in.left.full;
         }
         return;
@@ -113,10 +113,10 @@ template <class M> class RuleScore {
 
       float backoffs[KENLM_MAX_ORDER - 1], backoffs2[KENLM_MAX_ORDER - 1];
       float *back = backoffs, *back2 = backoffs2;
-      unsigned char next_use = out_.right.length;
+      unsigned char next_use = out_->right.length;
 
       // First word
-      if (ExtendLeft(in, next_use, 1, out_.right.backoff, back)) return;
+      if (ExtendLeft(in, next_use, 1, out_->right.backoff, back)) return;
 
       // Words after the first, so extending a bigram to begin with
       for (unsigned char extend_length = 2; extend_length <= in.left.length; ++extend_length) {
@@ -127,54 +127,58 @@ template <class M> class RuleScore {
       if (in.left.full) {
         for (const float *i = back; i != back + next_use; ++i) prob_ += *i;
         left_done_ = true;
-        out_.right = in.right;
+        out_->right = in.right;
         return;
       }
 
       // Right state was minimized, so it's already independent of the new words to the left.  
       if (in.right.length < in.left.length) {
-        out_.right = in.right;
+        out_->right = in.right;
         return;
       }
 
       // Shift exisiting words down.  
-      for (WordIndex *i = out_.right.words + next_use - 1; i >= out_.right.words; --i) {
+      for (WordIndex *i = out_->right.words + next_use - 1; i >= out_->right.words; --i) {
         *(i + in.right.length) = *i;
       }
       // Add words from in.right.  
-      std::copy(in.right.words, in.right.words + in.right.length, out_.right.words);
+      std::copy(in.right.words, in.right.words + in.right.length, out_->right.words);
       // Assemble backoff composed on the existing state's backoff followed by the new state's backoff.  
-      std::copy(in.right.backoff, in.right.backoff + in.right.length, out_.right.backoff);
-      std::copy(back, back + next_use, out_.right.backoff + in.right.length);
-      out_.right.length = in.right.length + next_use;
+      std::copy(in.right.backoff, in.right.backoff + in.right.length, out_->right.backoff);
+      std::copy(back, back + next_use, out_->right.backoff + in.right.length);
+      out_->right.length = in.right.length + next_use;
     }
 
     float Finish() {
       // A N-1-gram might extend left and right but we should still set full to true because it's an N-1-gram.  
-      out_.left.full = left_done_ || (out_.left.length == model_.Order() - 1);
+      out_->left.full = left_done_ || (out_->left.length == model_.Order() - 1);
       return prob_;
     }
 
     void Reset() {
       prob_ = 0.0;
       left_done_ = false;
-      out_.left.length = 0;
-      out_.right.length = 0;
+      out_->left.length = 0;
+      out_->right.length = 0;
+    }
+    void Reset(ChartState &replacement) {
+      out_ = &replacement;
+      Reset();
     }
 
   private:
     bool ExtendLeft(const ChartState &in, unsigned char &next_use, unsigned char extend_length, const float *back_in, float *back_out) {
       ProcessRet(model_.ExtendLeft(
-            out_.right.words, out_.right.words + next_use, // Words to extend into
+            out_->right.words, out_->right.words + next_use, // Words to extend into
             back_in, // Backoffs to use
             in.left.pointers[extend_length - 1], extend_length, // Words to be extended
             back_out, // Backoffs for the next score
             next_use)); // Length of n-gram to use in next scoring.  
-      if (next_use != out_.right.length) {
+      if (next_use != out_->right.length) {
         left_done_ = true;
         if (!next_use) {
           // Early exit.  
-          out_.right = in.right;
+          out_->right = in.right;
           prob_ += model_.UnRest(in.left.pointers + extend_length, in.left.pointers + in.left.length, extend_length + 1);
           return true;
         }
@@ -193,13 +197,13 @@ template <class M> class RuleScore {
         left_done_ = true;
         return;
       }
-      out_.left.pointers[out_.left.length++] = ret.extend_left;
+      out_->left.pointers[out_->left.length++] = ret.extend_left;
       prob_ += ret.rest;
     }
 
     const M &model_;
 
-    ChartState &out_;
+    ChartState *out_;
 
     bool left_done_;
 
diff --git a/klm/lm/max_order.hh b/klm/lm/max_order.hh
index 989f8324..ea0dea46 100644
--- a/klm/lm/max_order.hh
+++ b/klm/lm/max_order.hh
@@ -4,9 +4,8 @@
  * (kMaxOrder - 1) * sizeof(float) bytes instead of
  * sizeof(float*) + (kMaxOrder - 1) * sizeof(float) + malloc overhead
  */
-#ifndef KENLM_MAX_ORDER
-#define KENLM_MAX_ORDER 6
-#endif
 #ifndef KENLM_ORDER_MESSAGE
-#define KENLM_ORDER_MESSAGE "If your build system supports changing KENLM_MAX_ORDER, change it there and recompile.  In the KenLM tarball or Moses, use e.g. `bjam --kenlm-max-order=6 -a'.  Otherwise, edit lm/max_order.hh."
+#define KENLM_ORDER_MESSAGE "If your build system supports changing KENLM_MAX_ORDER, change it there and recompile.  In the KenLM tarball or Moses, use e.g. `bjam --max-kenlm-order=6 -a'.  Otherwise, edit lm/max_order.hh."
 #endif
+
+#define KENLM_MAX_ORDER 5
diff --git a/klm/lm/model.cc b/klm/lm/model.cc
index 2fd20481..fc61efee 100644
--- a/klm/lm/model.cc
+++ b/klm/lm/model.cc
@@ -87,7 +87,7 @@ template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT
       WriteWordsWrapper wrap(config.enumerate_vocab);
       vocab_.ConfigureEnumerate(&wrap, counts[0]);
       search_.InitializeFromARPA(file, f, counts, config, vocab_, backing_);
-      wrap.Write(backing_.file.get(), backing_.vocab.size() + vocab_.UnkCountChangePadding() + backing_.search.size());
+      wrap.Write(backing_.file.get(), backing_.vocab.size() + vocab_.UnkCountChangePadding() + Search::Size(counts, config));
     } else {
       vocab_.ConfigureEnumerate(config.enumerate_vocab, counts[0]);
       search_.InitializeFromARPA(file, f, counts, config, vocab_, backing_);
@@ -227,6 +227,7 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
     const WordIndex *const context_rend,
     const WordIndex new_word,
     State &out_state) const {
+  assert(new_word < vocab_.Bound());
   FullScoreReturn ret;
   // ret.ngram_length contains the last known non-blank ngram length.  
   ret.ngram_length = 1;
diff --git a/klm/lm/search_hashed.cc b/klm/lm/search_hashed.cc
index a1623834..2d6f15b2 100644
--- a/klm/lm/search_hashed.cc
+++ b/klm/lm/search_hashed.cc
@@ -231,7 +231,7 @@ template <class Value> void HashedSearch<Value>::InitializeFromARPA(const char *
 
 template <> void HashedSearch<BackoffValue>::DispatchBuild(util::FilePiece &f, const std::vector<uint64_t> &counts, const Config &config, const ProbingVocabulary &vocab, PositiveProbWarn &warn) {
   NoRestBuild build;
-  ApplyBuild(f, counts, config, vocab, warn, build);
+  ApplyBuild(f, counts, vocab, warn, build);
 }
 
 template <> void HashedSearch<RestValue>::DispatchBuild(util::FilePiece &f, const std::vector<uint64_t> &counts, const Config &config, const ProbingVocabulary &vocab, PositiveProbWarn &warn) {
@@ -239,19 +239,19 @@ template <> void HashedSearch<RestValue>::DispatchBuild(util::FilePiece &f, cons
     case Config::REST_MAX:
       {
         MaxRestBuild build;
-        ApplyBuild(f, counts, config, vocab, warn, build);
+        ApplyBuild(f, counts, vocab, warn, build);
       }
       break;
     case Config::REST_LOWER:
       {
         LowerRestBuild<ProbingModel> build(config, counts.size(), vocab);
-        ApplyBuild(f, counts, config, vocab, warn, build);
+        ApplyBuild(f, counts, vocab, warn, build);
       }
       break;
   }
 }
 
-template <class Value> template <class Build> void HashedSearch<Value>::ApplyBuild(util::FilePiece &f, const std::vector<uint64_t> &counts, const Config &config, const ProbingVocabulary &vocab, PositiveProbWarn &warn, const Build &build) {
+template <class Value> template <class Build> void HashedSearch<Value>::ApplyBuild(util::FilePiece &f, const std::vector<uint64_t> &counts, const ProbingVocabulary &vocab, PositiveProbWarn &warn, const Build &build) {
   for (WordIndex i = 0; i < counts[0]; ++i) {
     build.SetRest(&i, (unsigned int)1, unigram_.Raw()[i]);
   }
diff --git a/klm/lm/search_hashed.hh b/klm/lm/search_hashed.hh
index a52f107b..00595796 100644
--- a/klm/lm/search_hashed.hh
+++ b/klm/lm/search_hashed.hh
@@ -147,7 +147,7 @@ template <class Value> class HashedSearch {
     // Interpret config's rest cost build policy and pass the right template argument to ApplyBuild.  
     void DispatchBuild(util::FilePiece &f, const std::vector<uint64_t> &counts, const Config &config, const ProbingVocabulary &vocab, PositiveProbWarn &warn);
 
-    template <class Build> void ApplyBuild(util::FilePiece &f, const std::vector<uint64_t> &counts, const Config &config, const ProbingVocabulary &vocab, PositiveProbWarn &warn, const Build &build);
+    template <class Build> void ApplyBuild(util::FilePiece &f, const std::vector<uint64_t> &counts, const ProbingVocabulary &vocab, PositiveProbWarn &warn, const Build &build);
 
     class Unigram {
       public:
diff --git a/klm/lm/vocab.cc b/klm/lm/vocab.cc
index 11c27518..fd7f96dc 100644
--- a/klm/lm/vocab.cc
+++ b/klm/lm/vocab.cc
@@ -116,7 +116,9 @@ WordIndex SortedVocabulary::Insert(const StringPiece &str) {
   }
   *end_ = hashed;
   if (enumerate_) {
-    strings_to_enumerate_[end_ - begin_].assign(str.data(), str.size());
+    void *copied = string_backing_.Allocate(str.size());
+    memcpy(copied, str.data(), str.size());
+    strings_to_enumerate_[end_ - begin_] = StringPiece(static_cast<const char*>(copied), str.size());
   }
   ++end_;
   // This is 1 + the offset where it was inserted to make room for unk.  
@@ -126,7 +128,7 @@ WordIndex SortedVocabulary::Insert(const StringPiece &str) {
 void SortedVocabulary::FinishedLoading(ProbBackoff *reorder_vocab) {
   if (enumerate_) {
     if (!strings_to_enumerate_.empty()) {
-      util::PairedIterator<ProbBackoff*, std::string*> values(reorder_vocab + 1, &*strings_to_enumerate_.begin());
+      util::PairedIterator<ProbBackoff*, StringPiece*> values(reorder_vocab + 1, &*strings_to_enumerate_.begin());
       util::JointSort(begin_, end_, values);
     }
     for (WordIndex i = 0; i < static_cast<WordIndex>(end_ - begin_); ++i) {
@@ -134,6 +136,7 @@ void SortedVocabulary::FinishedLoading(ProbBackoff *reorder_vocab) {
       enumerate_->Add(i + 1, strings_to_enumerate_[i]);
     }
     strings_to_enumerate_.clear();
+    string_backing_.FreeAll();
   } else {
     util::JointSort(begin_, end_, reorder_vocab + 1);
   }
diff --git a/klm/lm/vocab.hh b/klm/lm/vocab.hh
index de54eb06..3902f117 100644
--- a/klm/lm/vocab.hh
+++ b/klm/lm/vocab.hh
@@ -4,6 +4,7 @@
 #include "lm/enumerate_vocab.hh"
 #include "lm/lm_exception.hh"
 #include "lm/virtual_interface.hh"
+#include "util/pool.hh"
 #include "util/probing_hash_table.hh"
 #include "util/sorted_uniform.hh"
 #include "util/string_piece.hh"
@@ -96,7 +97,9 @@ class SortedVocabulary : public base::Vocabulary {
     EnumerateVocab *enumerate_;
 
     // Actual strings.  Used only when loading from ARPA and enumerate_ != NULL 
-    std::vector<std::string> strings_to_enumerate_;
+    util::Pool string_backing_;
+
+    std::vector<StringPiece> strings_to_enumerate_;
 };
 
 #pragma pack(push)
diff --git a/klm/search/Makefile.am b/klm/search/Makefile.am
index ccc5b7f6..5aea33c2 100644
--- a/klm/search/Makefile.am
+++ b/klm/search/Makefile.am
@@ -2,10 +2,10 @@ noinst_LIBRARIES = libksearch.a
 
 libksearch_a_SOURCES = \
   edge_generator.cc \
+	nbest.cc \
   rule.cc \
   vertex.cc \
-  vertex_generator.cc \
-  weights.cc
+  vertex_generator.cc
 
 AM_CPPFLAGS = -W -Wall -Wno-sign-compare $(GTEST_CPPFLAGS) -I..
 
diff --git a/klm/search/applied.hh b/klm/search/applied.hh
new file mode 100644
index 00000000..bd659e5c
--- /dev/null
+++ b/klm/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/klm/search/config.hh b/klm/search/config.hh
index ef8e2354..ba18c09e 100644
--- a/klm/search/config.hh
+++ b/klm/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/klm/search/context.hh b/klm/search/context.hh
index 62163144..08f21bbf 100644
--- a/klm/search/context.hh
+++ b/klm/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(); }
 
-  private:
-    util::Pool final_pool_;
+    const Config &GetConfig() const { return config_; }
 
+  private:
     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/klm/search/dedupe.hh b/klm/search/dedupe.hh
new file mode 100644
index 00000000..7eaa3b95
--- /dev/null
+++ b/klm/search/dedupe.hh
@@ -0,0 +1,131 @@
+#ifndef SEARCH_DEDUPE__
+#define SEARCH_DEDUPE__
+
+#include "lm/state.hh"
+#include "search/edge_generator.hh"
+
+#include <boost/pool/object_pool.hpp>
+#include <boost/unordered_map.hpp>
+
+namespace search {
+
+class Dedupe {
+  public:
+    Dedupe() {}
+
+    PartialEdge AllocateEdge(Arity arity) {
+      return behind_.AllocateEdge(arity);
+    }
+
+    void AddEdge(PartialEdge edge) {
+      edge.MutableFlags() = 0;
+
+      uint64_t hash = 0;
+      const PartialVertex *v = edge.NT();
+      const PartialVertex *v_end = v + edge.GetArity();
+      for (; v != v_end; ++v) {
+        const void *ptr = v->Identify();
+        hash = util::MurmurHashNative(&ptr, sizeof(const void*), hash);
+      }
+      
+      const lm::ngram::ChartState *c = edge.Between();
+      const lm::ngram::ChartState *const c_end = c + edge.GetArity() + 1;
+      for (; c != c_end; ++c) hash = hash_value(*c, hash);
+
+      std::pair<Table::iterator, bool> ret(table_.insert(std::make_pair(hash, edge)));
+      if (!ret.second) FoundDupe(ret.first->second, edge);
+    }
+
+    bool Empty() const { return behind_.Empty(); }
+
+    template <class Model, class Output> void Search(Context<Model> &context, Output &output) {
+      for (Table::const_iterator i(table_.begin()); i != table_.end(); ++i) {
+        behind_.AddEdge(i->second);
+      }
+      Unpack<Output> unpack(output, *this);
+      behind_.Search(context, unpack);
+    }
+
+  private:
+    void FoundDupe(PartialEdge &table, PartialEdge adding) {
+      if (table.GetFlags() & kPackedFlag) {
+        Packed &packed = *static_cast<Packed*>(table.GetNote().mut);
+        if (table.GetScore() >= adding.GetScore()) {
+          packed.others.push_back(adding);
+          return;
+        }
+        Note original(packed.original);
+        packed.original = adding.GetNote();
+        adding.SetNote(table.GetNote());
+        table.SetNote(original);
+        packed.others.push_back(table);
+        packed.starting = adding.GetScore();
+        table = adding;
+        table.MutableFlags() |= kPackedFlag;
+        return;
+      }
+      PartialEdge loser;
+      if (adding.GetScore() > table.GetScore()) {
+        loser = table;
+        table = adding;
+      } else {
+        loser = adding;
+      }
+      // table is winner, loser is loser...
+      packed_.construct(table, loser);
+    }
+
+    struct Packed {
+      Packed(PartialEdge winner, PartialEdge loser) 
+        : original(winner.GetNote()), starting(winner.GetScore()), others(1, loser) {
+        winner.MutableNote().vp = this;
+        winner.MutableFlags() |= kPackedFlag;
+        loser.MutableFlags() &= ~kPackedFlag;
+      }
+      Note original;
+      Score starting;
+      std::vector<PartialEdge> others;
+    };
+
+    template <class Output> class Unpack {
+      public:
+        explicit Unpack(Output &output, Dedupe &owner) : output_(output), owner_(owner) {}
+
+        void NewHypothesis(PartialEdge edge) {
+          if (edge.GetFlags() & kPackedFlag) {
+            Packed &packed = *reinterpret_cast<Packed*>(edge.GetNote().mut);
+            edge.SetNote(packed.original);
+            edge.MutableFlags() = 0;
+            std::size_t copy_size = sizeof(PartialVertex) * edge.GetArity() + sizeof(lm::ngram::ChartState);
+            for (std::vector<PartialEdge>::iterator i = packed.others.begin(); i != packed.others.end(); ++i) {
+              PartialEdge copy(owner_.AllocateEdge(edge.GetArity()));
+              copy.SetScore(edge.GetScore() - packed.starting + i->GetScore());
+              copy.MutableFlags() = 0;
+              copy.SetNote(i->GetNote());
+              memcpy(copy.NT(), edge.NT(), copy_size);
+              output_.NewHypothesis(copy);
+            }
+          }
+          output_.NewHypothesis(edge);
+        }
+
+        void FinishedSearch() {
+          output_.FinishedSearch();
+        }
+
+      private:
+        Output &output_;
+        Dedupe &owner_;
+    };
+
+    EdgeGenerator behind_;
+
+    typedef boost::unordered_map<uint64_t, PartialEdge> Table;
+    Table table_;
+
+    boost::object_pool<Packed> packed_;
+
+    static const uint16_t kPackedFlag = 1;
+};
+} // namespace search
+#endif // SEARCH_DEDUPE__
diff --git a/klm/search/edge_generator.cc b/klm/search/edge_generator.cc
index 260159b1..eacf5de5 100644
--- a/klm/search/edge_generator.cc
+++ b/klm/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/klm/search/edge_generator.hh b/klm/search/edge_generator.hh
index 582c78b7..203942c6 100644
--- a/klm/search/edge_generator.hh
+++ b/klm/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/klm/search/final.hh b/klm/search/final.hh
deleted file mode 100644
index 50e62cf2..00000000
--- a/klm/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/klm/search/header.hh b/klm/search/header.hh
index 25550dbe..69f0eed0 100644
--- a/klm/search/header.hh
+++ b/klm/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/klm/search/nbest.cc b/klm/search/nbest.cc
new file mode 100644
index 00000000..ec3322c9
--- /dev/null
+++ b/klm/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/klm/search/nbest.hh b/klm/search/nbest.hh
new file mode 100644
index 00000000..cb7651bc
--- /dev/null
+++ b/klm/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/klm/search/note.hh b/klm/search/note.hh
deleted file mode 100644
index 50bed06e..00000000
--- a/klm/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/klm/search/rule.cc b/klm/search/rule.cc
index 5b00207e..0244a09f 100644
--- a/klm/search/rule.cc
+++ b/klm/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/klm/search/rule.hh b/klm/search/rule.hh
index 0ce2794d..43ca6162 100644
--- a/klm/search/rule.hh
+++ b/klm/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/klm/search/types.hh b/klm/search/types.hh
index 06eb5bfa..f9c849b3 100644
--- a/klm/search/types.hh
+++ b/klm/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/klm/search/vertex.cc b/klm/search/vertex.cc
index 11f4631f..45842982 100644
--- a/klm/search/vertex.cc
+++ b/klm/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/klm/search/vertex.hh b/klm/search/vertex.hh
index 52bc1dfe..10b3339b 100644
--- a/klm/search/vertex.hh
+++ b/klm/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/klm/search/vertex_generator.cc b/klm/search/vertex_generator.cc
index 0945fe55..73139ffc 100644
--- a/klm/search/vertex_generator.cc
+++ b/klm/search/vertex_generator.cc
@@ -4,26 +4,18 @@
 #include "search/context.hh"
 #include "search/edge.hh"
 
+#include <boost/unordered_map.hpp>
+#include <boost/version.hpp>
+
 #include <stdint.h>
 
 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) {
@@ -39,19 +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();
-
-  starter.under->SetEnd(final);
-}
+} // namespace
 
-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;
@@ -77,18 +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);
+  node->under->SetEnd(end.history, end.score);
 }
 
-} // namespace
-
-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);
-}
+#endif // BOOST_VERSION
 
 } // namespace search
diff --git a/klm/search/vertex_generator.hh b/klm/search/vertex_generator.hh
index 60e86112..da563c2d 100644
--- a/klm/search/vertex_generator.hh
+++ b/klm/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);
+    VertexGenerator(ContextBase &context, Vertex &gen, Output &nbest) : context_(context), gen_(gen), nbest_(nbest) {
+      gen.root_.InitRoot();
+    }
 
     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;
-      }
+      nbest_.Add(existing_[hash_value(partial.CompletedState())], partial);
     }
 
-    void FinishedSearch();
+    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/klm/search/weights.cc b/klm/search/weights.cc
deleted file mode 100644
index d65471ad..00000000
--- a/klm/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/klm/search/weights.hh b/klm/search/weights.hh
deleted file mode 100644
index df1c419f..00000000
--- a/klm/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/klm/search/weights_test.cc b/klm/search/weights_test.cc
deleted file mode 100644
index 4811ff06..00000000
--- a/klm/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