Esempio n. 1
0
    public Tree<String> getBestParseOld(List<String> sentence) {
      // TODO: This implements the CKY algorithm

      CounterMap<String, String> parseScores = new CounterMap<String, String>();

      System.out.println(sentence.toString());
      // First deal with the lexicons
      int index = 0;
      int span = 1; // All spans are 1 at the lexicon level
      for (String word : sentence) {
        for (String tag : lexicon.getAllTags()) {
          double score = lexicon.scoreTagging(word, tag);
          if (score >= 0.0) { // This lexicon may generate this word
            // We use a counter map in order to store the scores for this sentence parse.
            parseScores.setCount(index + " " + (index + span), tag, score);
          }
        }
        index = index + 1;
      }

      // handle unary rules now
      HashMap<String, Triplet<Integer, String, String>> backHash =
          new HashMap<
              String, Triplet<Integer, String, String>>(); // hashmap to store back propation

      // System.out.println("Lexicons found");
      Boolean added = true;

      while (added) {
        added = false;
        for (index = 0; index < sentence.size(); index++) {
          // For each index+ span pair, get the counter.
          Counter<String> count = parseScores.getCounter(index + " " + (index + span));
          PriorityQueue<String> countAsPQ = count.asPriorityQueue();
          while (countAsPQ.hasNext()) {
            String entry = countAsPQ.next();
            // System.out.println("I am fine here!!");
            List<UnaryRule> unaryRules = grammar.getUnaryRulesByChild(entry);
            for (UnaryRule rule : unaryRules) {
              // These are the unary rules which might give rise to the above preterminal
              double prob =
                  rule.getScore() * parseScores.getCount(index + " " + (index + span), entry);
              if (prob > parseScores.getCount(index + " " + (index + span), rule.parent)) {
                parseScores.setCount(index + " " + (index + span), rule.parent, prob);
                backHash.put(
                    index + " " + (index + span) + " " + rule.parent,
                    new Triplet<Integer, String, String>(-1, entry, null));
                added = true;
              }
            }
          }
        }
      }
      // System.out.println("Lexicon unaries dealt with");

      // Now work with the grammar to produce higher level probabilities
      for (span = 2; span <= sentence.size(); span++) {
        for (int begin = 0; begin <= (sentence.size() - span); begin++) {
          int end = begin + span;
          for (int split = begin + 1; split <= end - 1; split++) {
            Counter<String> countLeft = parseScores.getCounter(begin + " " + split);
            Counter<String> countRight = parseScores.getCounter(split + " " + end);
            // List<BinaryRule> leftRules= new ArrayList<BinaryRule>();
            HashMap<Integer, BinaryRule> leftMap = new HashMap<Integer, BinaryRule>();
            // List<BinaryRule> rightRules=new ArrayList<BinaryRule>();
            HashMap<Integer, BinaryRule> rightMap = new HashMap<Integer, BinaryRule>();

            for (String entry : countLeft.keySet()) {
              for (BinaryRule rule : grammar.getBinaryRulesByLeftChild(entry)) {
                if (!leftMap.containsKey(rule.hashCode())) {
                  leftMap.put(rule.hashCode(), rule);
                }
              }
            }

            for (String entry : countRight.keySet()) {
              for (BinaryRule rule : grammar.getBinaryRulesByRightChild(entry)) {
                if (!rightMap.containsKey(rule.hashCode())) {
                  rightMap.put(rule.hashCode(), rule);
                }
              }
            }

            // System.out.println("About to enter the rules loops");
            for (Integer ruleHash : leftMap.keySet()) {
              if (rightMap.containsKey(ruleHash)) {
                BinaryRule ruleRight = rightMap.get(ruleHash);
                double prob =
                    ruleRight.getScore()
                        * parseScores.getCount(begin + " " + split, ruleRight.leftChild)
                        * parseScores.getCount(split + " " + end, ruleRight.rightChild);
                // System.out.println(begin+" "+ end +" "+ ruleRight.parent+ " "+ prob);
                if (prob > parseScores.getCount(begin + " " + end, ruleRight.parent)) {
                  // System.out.println(begin+" "+ end +" "+ ruleRight.parent+ " "+ prob);
                  // System.out.println("parentrule :"+ ruleRight.getParent());
                  parseScores.setCount(begin + " " + end, ruleRight.getParent(), prob);
                  backHash.put(
                      begin + " " + end + " " + ruleRight.parent,
                      new Triplet<Integer, String, String>(
                          split, ruleRight.leftChild, ruleRight.rightChild));
                }
              }
            }

            // System.out.println("Exited rules loop");

          }
          // System.out.println("Grammar found for " + begin + " "+ end);
          // Now handle unary rules
          added = true;
          while (added) {
            added = false;
            Counter<String> count = parseScores.getCounter(begin + " " + end);
            PriorityQueue<String> countAsPriorityQueue = count.asPriorityQueue();
            while (countAsPriorityQueue.hasNext()) {
              String entry = countAsPriorityQueue.next();
              List<UnaryRule> unaryRules = grammar.getUnaryRulesByChild(entry);
              for (UnaryRule rule : unaryRules) {
                double prob = rule.getScore() * parseScores.getCount(begin + " " + (end), entry);
                if (prob > parseScores.getCount(begin + " " + (end), rule.parent)) {
                  parseScores.setCount(begin + " " + (end), rule.parent, prob);

                  backHash.put(
                      begin + " " + (end) + " " + rule.parent,
                      new Triplet<Integer, String, String>(-1, entry, null));
                  added = true;
                }
              }
            }
          }

          // System.out.println("Unaries dealt for " + begin + " "+ end);

        }
      }

      // Create and return the parse tree
      Tree<String> parseTree = new Tree<String>("null");
      // System.out.println(parseScores.getCounter(0+" "+sentence.size()).toString());
      String parent = parseScores.getCounter(0 + " " + sentence.size()).argMax();
      if (parent == null) {
        System.out.println(parseScores.getCounter(0 + " " + sentence.size()).toString());
        System.out.println("THIS IS WEIRD");
      }
      parent = "ROOT";
      parseTree = getParseTreeOld(sentence, backHash, 0, sentence.size(), parent);
      // System.out.println("PARSE SCORES");
      //	System.out.println(parseScores.toString());
      // System.out.println("BACK HASH");
      // System.out.println(backHash.toString());
      //	parseTree = addRoot(parseTree);
      // System.out.println(parseTree.toString());
      // return parseTree;
      return TreeAnnotations.unAnnotateTree(parseTree);
    }
Esempio n. 2
0
 public void setTransitionCount(S start, S end, double count) {
   forwardTransitions.setCount(start, end, count);
   backwardTransitions.setCount(end, start, count);
 }
	  private CounterMap<String,String> trainEM(int maxIterations) {
		  Set<String> englishVocab = new HashSet<String>();
		  Set<String> frenchVocab = new HashSet<String>();
		  
		  CounterMap<String,String> translations = new CounterMap<String,String>();
		  englishVocab.add(NULL);
		  int iteration = 0;
		  final double thresholdProb = 0.0001;
		  
		  for (SentencePair sentencePair : trainingSentencePairs) {
			  List<String> frenchWords = sentencePair.getFrenchWords();
			  List<String> englishWords = sentencePair.getEnglishWords();
			  // add words from list to vocabulary sets
			  englishVocab.addAll(englishWords);
			  frenchVocab.addAll(frenchWords);
		  }
		  System.out.println("Ready");
		  
		  // We need to initialize translations.getCount(f,e) uniformly
		  // t(f|e) summed over all e in {E + NULL} = 1
		  final double initialCount = 1.0 / englishVocab.size();
		  
		  while(iteration < maxIterations) {
			  CounterMap<String,String> counts = new CounterMap<String,String>(); // set count(f|e) to 0 for all e,f
			  Counter<String> totalEnglish = new Counter<String>(); // set total(e) to 0 for all e
			  
			  // E-step: loop over all sentences and update counts
			  for (SentencePair sentencePair : trainingSentencePairs) {
				  List<String> frenchWords = sentencePair.getFrenchWords();
				  List<String> englishWords = sentencePair.getEnglishWords();
				  
			      int numFrenchWords = frenchWords.size();
			      int numEnglishWords = englishWords.size();
			      Counter<String> sTotalF = new Counter<String>(); 
			      
			      // compute normalization constant sTotalF
			      for (int frenchPosition = 0; frenchPosition < numFrenchWords; frenchPosition++) {
			    	  String f = frenchWords.get(frenchPosition);
			    	  // initialize and compute for English = NULL
			    	  if (!translations.containsKey(f) && initialize)
			    		  translations.setCount(f, NULL, initialCount);
			    	  else if (!translations.containsKey(f))
			    		  translations.setCount(f, NULL, thresholdProb);
			    	  sTotalF.incrementCount(f, translations.getCount(f, NULL)); 
			    	  for (int englishPosition = 0; englishPosition < numEnglishWords; englishPosition++) {
			    		  String e = englishWords.get(englishPosition);
			    		  if (!(translations.getCounter(f)).containsKey(e) && initialize)
			    			  translations.setCount(f, e, initialCount);
			    		  else if (!(translations.getCounter(f)).containsKey(e))
			    			  translations.setCount(f, e, thresholdProb);
			    		  sTotalF.incrementCount(f, translations.getCount(f, e));
			    	  }
			      }
			      
			      // collect counts in counts and totalEnglish
			      for (int frenchPosition = 0; frenchPosition < numFrenchWords; frenchPosition++) {
			    	  String f = frenchWords.get(frenchPosition);
			    	  
			    	  // collect counts for English = NULL
			    	  double count = translations.getCount(f, NULL) / sTotalF.getCount(f);
			    	  counts.incrementCount(NULL, f, count);
			    	  totalEnglish.incrementCount(NULL, count);
			    	  for (int englishPosition = 0; englishPosition < numEnglishWords; englishPosition++) {
			    		  String e = englishWords.get(englishPosition);
			    		  count = translations.getCount(f, e) / sTotalF.getCount(f);
			    		  counts.incrementCount(e, f, count);
			    		  totalEnglish.incrementCount(e, count);
			    	  }
			      }
			  } // end of E-step
			  System.out.println("Completed E-step");
			  
			  // M-step: update probabilities with counts from E-step and check for convergence
			  iteration++;
			  for (String e : counts.keySet()) {//englishVocab) {
				  double normalizer = totalEnglish.getCount(e);
				  for (String f : (counts.getCounter(e)).keySet()) {//frenchVocab) {
					  
					  // To speed implementation, we want to update translations only when count / normalizer > threshold
					  double prob = counts.getCount(e, f) / normalizer;
					  if (!initialize) {					  
						  if (prob > thresholdProb)
							  translations.setCount(f, e, prob);
						  else
							  (translations.getCounter(f)).removeKey(e);
					  }
					  else {
						  translations.setCount(f, e, prob);
					  }
				  }
			  }
			  System.out.println("Completed iteration " + iteration);
		  } // end of M-step
		  
		  System.out.println("Trained!");
		  return translations;
	  }