public static ArrayList<TaggedWord> StanfordParse(String sentence, LexicalizedParser lp) {

    TokenizerFactory<CoreLabel> tokenizerFactory =
        PTBTokenizer.factory(new CoreLabelTokenFactory(), "");
    List<CoreLabel> rawWords2 =
        tokenizerFactory.getTokenizer(new StringReader(sentence)).tokenize();
    Tree parse = lp.apply(rawWords2);
    ArrayList<TaggedWord> taggedWords = parse.taggedYield();

    return taggedWords;
  }
  private ArrayList<TaggedWord> parseSentenceTD(String text) {
    System.out.println("Parsing sentence...");

    ArrayList<TaggedWord> tw = new ArrayList<TaggedWord>();

    Reader reader = new StringReader(text);

    for (List<HasWord> sentence : new DocumentPreprocessor(reader)) {

      Tree parse = lp.apply(sentence);

      tw = parse.taggedYield();
    }
    return tw;
  }
  public static ArrayList<ArrayList<TaggedWord>> getPhrases(Tree parse, int phraseSizeLimit) {
    ArrayList<ArrayList<TaggedWord>> newList = new ArrayList<ArrayList<TaggedWord>>();
    List<Tree> leaves = parse.getLeaves();

    if (leaves.size() <= phraseSizeLimit) {
      // ArrayList<TaggedWord> phraseElements = PreprocessPhrase(parse.taggedYield());
      ArrayList<TaggedWord> phraseElements = Preprocess(parse.taggedYield());
      if (phraseElements.size() > 0) newList.add(phraseElements);
    } else {
      Tree[] childrenNodes = parse.children();
      for (int i = 0; i < childrenNodes.length; i++) {
        Tree currentParse = childrenNodes[i];
        newList.addAll(getPhrases(currentParse, phraseSizeLimit));
      }
    }
    return newList;
  }
 public static void main(String args[]) {
   //        String sentence1 = "A large bird standing on a table picks up a plastic glass
   // containing liquid and places it in a bowl of something.";
   //        String sentence2 = "A bird picks up a plastic cup containing a liquid with it's beak
   // and puts the cup into a bowl.";
   //        LexicalizedParser lp = new LexicalizedParser("englishPCFG.ser.gz");
   //        LeskWSD tm = new LeskWSD(lp);
   //        WordNetSimilarity ws = new WordNetSimilarity();
   //
   //        System.out.println(LexicalSimilarityScoreWordNet(sentence1, sentence2, tm, lp, ws));
   String sentence =
       "The broader Standard & Poor's 500 Index <.SPX> shed 2.38 points, or 0.24 percent, at 995.10.";
   LexicalizedParser lp = new LexicalizedParser("englishPCFG.ser.gz");
   Tree parse = lp.apply(sentence);
   ArrayList<TaggedWord> taggedWords = parse.taggedYield();
   taggedWords = Preprocess(taggedWords);
   for (int i = 0; i < taggedWords.size(); i++) System.out.println(taggedWords.get(i).word());
 }
Пример #5
0
  public LinkedList<String> getKeyWrodsFromSentenceTest(String string) {

    LinkedList<String> list = new LinkedList<String>();

    String[] sent = string.split(" ");
    List<HasWord> sentence = new ArrayList<HasWord>();
    for (String word : sent) {
      sentence.add(new Word(word));
    }

    Tree parse = lp.parse(sentence);
    parse.pennPrint();
    GrammaticalStructure gs = gsf.newGrammaticalStructure(parse);

    List<TypedDependency> tdl = gs.typedDependenciesCCprocessed();
    System.out.println(tdl);

    System.out.println();

    System.out.println("The words of the sentence:");
    for (Label lab : parse.yield()) {
      if (lab instanceof CoreLabel) {
        System.out.println(((CoreLabel) lab).toString(CoreLabel.OutputFormat.VALUE_MAP));
      } else {
        System.out.println(lab);
      }
    }
    System.out.println();
    System.out.println("tagged");
    System.out.println(parse.taggedYield());

    List<CoreLabel> temp = parse.taggedLabeledYield();
    for (Label l : temp) {
      String[] sss = l.toString().split("-");
      String type = sss[0];
      System.out.println(sss[0] + "  " + sss[1] + "    " + sent[Integer.parseInt(sss[1])]);
    }

    for (Iterator<String> ite = list.iterator(); ite.hasNext(); ) System.out.println(ite.next());
    return list;
  }
Пример #6
0
 /** Set the tags of the original tokens and the leaves if they aren't already set */
 public static void setMissingTags(CoreMap sentence, Tree tree) {
   List<TaggedWord> taggedWords = null;
   List<Label> leaves = null;
   List<CoreLabel> tokens = sentence.get(TokensAnnotation.class);
   for (int i = 0; i < tokens.size(); ++i) {
     CoreLabel token = tokens.get(i);
     if (token.tag() == null) {
       if (taggedWords == null) {
         taggedWords = tree.taggedYield();
       }
       if (leaves == null) {
         leaves = tree.yield();
       }
       token.setTag(taggedWords.get(i).tag());
       Label leaf = leaves.get(i);
       if (leaf instanceof HasTag) {
         ((HasTag) leaf).setTag(taggedWords.get(i).tag());
       }
     }
   }
 }
Пример #7
0
  public static void main(String[] args) {
    Options op = new Options(new EnglishTreebankParserParams());
    // op.tlpParams may be changed to something else later, so don't use it till
    // after options are parsed.

    System.out.println(StringUtils.toInvocationString("FactoredParser", args));

    String path = "/u/nlp/stuff/corpora/Treebank3/parsed/mrg/wsj";
    int trainLow = 200, trainHigh = 2199, testLow = 2200, testHigh = 2219;
    String serializeFile = null;

    int i = 0;
    while (i < args.length && args[i].startsWith("-")) {
      if (args[i].equalsIgnoreCase("-path") && (i + 1 < args.length)) {
        path = args[i + 1];
        i += 2;
      } else if (args[i].equalsIgnoreCase("-train") && (i + 2 < args.length)) {
        trainLow = Integer.parseInt(args[i + 1]);
        trainHigh = Integer.parseInt(args[i + 2]);
        i += 3;
      } else if (args[i].equalsIgnoreCase("-test") && (i + 2 < args.length)) {
        testLow = Integer.parseInt(args[i + 1]);
        testHigh = Integer.parseInt(args[i + 2]);
        i += 3;
      } else if (args[i].equalsIgnoreCase("-serialize") && (i + 1 < args.length)) {
        serializeFile = args[i + 1];
        i += 2;
      } else if (args[i].equalsIgnoreCase("-tLPP") && (i + 1 < args.length)) {
        try {
          op.tlpParams = (TreebankLangParserParams) Class.forName(args[i + 1]).newInstance();
        } catch (ClassNotFoundException e) {
          System.err.println("Class not found: " + args[i + 1]);
          throw new RuntimeException(e);
        } catch (InstantiationException e) {
          System.err.println("Couldn't instantiate: " + args[i + 1] + ": " + e.toString());
          throw new RuntimeException(e);
        } catch (IllegalAccessException e) {
          System.err.println("illegal access" + e);
          throw new RuntimeException(e);
        }
        i += 2;
      } else if (args[i].equals("-encoding")) {
        // sets encoding for TreebankLangParserParams
        op.tlpParams.setInputEncoding(args[i + 1]);
        op.tlpParams.setOutputEncoding(args[i + 1]);
        i += 2;
      } else {
        i = op.setOptionOrWarn(args, i);
      }
    }
    // System.out.println(tlpParams.getClass());
    TreebankLanguagePack tlp = op.tlpParams.treebankLanguagePack();

    op.trainOptions.sisterSplitters =
        new HashSet<String>(Arrays.asList(op.tlpParams.sisterSplitters()));
    //    BinarizerFactory.TreeAnnotator.setTreebankLang(tlpParams);
    PrintWriter pw = op.tlpParams.pw();

    op.testOptions.display();
    op.trainOptions.display();
    op.display();
    op.tlpParams.display();

    // setup tree transforms
    Treebank trainTreebank = op.tlpParams.memoryTreebank();
    MemoryTreebank testTreebank = op.tlpParams.testMemoryTreebank();
    // Treebank blippTreebank = ((EnglishTreebankParserParams) tlpParams).diskTreebank();
    // String blippPath = "/afs/ir.stanford.edu/data/linguistic-data/BLLIP-WSJ/";
    // blippTreebank.loadPath(blippPath, "", true);

    Timing.startTime();
    System.err.print("Reading trees...");
    testTreebank.loadPath(path, new NumberRangeFileFilter(testLow, testHigh, true));
    if (op.testOptions.increasingLength) {
      Collections.sort(testTreebank, new TreeLengthComparator());
    }

    trainTreebank.loadPath(path, new NumberRangeFileFilter(trainLow, trainHigh, true));
    Timing.tick("done.");

    System.err.print("Binarizing trees...");
    TreeAnnotatorAndBinarizer binarizer;
    if (!op.trainOptions.leftToRight) {
      binarizer =
          new TreeAnnotatorAndBinarizer(
              op.tlpParams, op.forceCNF, !op.trainOptions.outsideFactor(), true, op);
    } else {
      binarizer =
          new TreeAnnotatorAndBinarizer(
              op.tlpParams.headFinder(),
              new LeftHeadFinder(),
              op.tlpParams,
              op.forceCNF,
              !op.trainOptions.outsideFactor(),
              true,
              op);
    }

    CollinsPuncTransformer collinsPuncTransformer = null;
    if (op.trainOptions.collinsPunc) {
      collinsPuncTransformer = new CollinsPuncTransformer(tlp);
    }
    TreeTransformer debinarizer = new Debinarizer(op.forceCNF);
    List<Tree> binaryTrainTrees = new ArrayList<Tree>();

    if (op.trainOptions.selectiveSplit) {
      op.trainOptions.splitters =
          ParentAnnotationStats.getSplitCategories(
              trainTreebank,
              op.trainOptions.tagSelectiveSplit,
              0,
              op.trainOptions.selectiveSplitCutOff,
              op.trainOptions.tagSelectiveSplitCutOff,
              op.tlpParams.treebankLanguagePack());
      if (op.trainOptions.deleteSplitters != null) {
        List<String> deleted = new ArrayList<String>();
        for (String del : op.trainOptions.deleteSplitters) {
          String baseDel = tlp.basicCategory(del);
          boolean checkBasic = del.equals(baseDel);
          for (Iterator<String> it = op.trainOptions.splitters.iterator(); it.hasNext(); ) {
            String elem = it.next();
            String baseElem = tlp.basicCategory(elem);
            boolean delStr = checkBasic && baseElem.equals(baseDel) || elem.equals(del);
            if (delStr) {
              it.remove();
              deleted.add(elem);
            }
          }
        }
        System.err.println("Removed from vertical splitters: " + deleted);
      }
    }
    if (op.trainOptions.selectivePostSplit) {
      TreeTransformer myTransformer =
          new TreeAnnotator(op.tlpParams.headFinder(), op.tlpParams, op);
      Treebank annotatedTB = trainTreebank.transform(myTransformer);
      op.trainOptions.postSplitters =
          ParentAnnotationStats.getSplitCategories(
              annotatedTB,
              true,
              0,
              op.trainOptions.selectivePostSplitCutOff,
              op.trainOptions.tagSelectivePostSplitCutOff,
              op.tlpParams.treebankLanguagePack());
    }

    if (op.trainOptions.hSelSplit) {
      binarizer.setDoSelectiveSplit(false);
      for (Tree tree : trainTreebank) {
        if (op.trainOptions.collinsPunc) {
          tree = collinsPuncTransformer.transformTree(tree);
        }
        // tree.pennPrint(tlpParams.pw());
        tree = binarizer.transformTree(tree);
        // binaryTrainTrees.add(tree);
      }
      binarizer.setDoSelectiveSplit(true);
    }
    for (Tree tree : trainTreebank) {
      if (op.trainOptions.collinsPunc) {
        tree = collinsPuncTransformer.transformTree(tree);
      }
      tree = binarizer.transformTree(tree);
      binaryTrainTrees.add(tree);
    }
    if (op.testOptions.verbose) {
      binarizer.dumpStats();
    }

    List<Tree> binaryTestTrees = new ArrayList<Tree>();
    for (Tree tree : testTreebank) {
      if (op.trainOptions.collinsPunc) {
        tree = collinsPuncTransformer.transformTree(tree);
      }
      tree = binarizer.transformTree(tree);
      binaryTestTrees.add(tree);
    }
    Timing.tick("done."); // binarization
    BinaryGrammar bg = null;
    UnaryGrammar ug = null;
    DependencyGrammar dg = null;
    // DependencyGrammar dgBLIPP = null;
    Lexicon lex = null;
    Index<String> stateIndex = new HashIndex<String>();

    // extract grammars
    Extractor<Pair<UnaryGrammar, BinaryGrammar>> bgExtractor =
        new BinaryGrammarExtractor(op, stateIndex);
    // Extractor bgExtractor = new SmoothedBinaryGrammarExtractor();//new BinaryGrammarExtractor();
    // Extractor lexExtractor = new LexiconExtractor();

    // Extractor dgExtractor = new DependencyMemGrammarExtractor();

    if (op.doPCFG) {
      System.err.print("Extracting PCFG...");
      Pair<UnaryGrammar, BinaryGrammar> bgug = null;
      if (op.trainOptions.cheatPCFG) {
        List<Tree> allTrees = new ArrayList<Tree>(binaryTrainTrees);
        allTrees.addAll(binaryTestTrees);
        bgug = bgExtractor.extract(allTrees);
      } else {
        bgug = bgExtractor.extract(binaryTrainTrees);
      }
      bg = bgug.second;
      bg.splitRules();
      ug = bgug.first;
      ug.purgeRules();
      Timing.tick("done.");
    }
    System.err.print("Extracting Lexicon...");
    Index<String> wordIndex = new HashIndex<String>();
    Index<String> tagIndex = new HashIndex<String>();
    lex = op.tlpParams.lex(op, wordIndex, tagIndex);
    lex.train(binaryTrainTrees);
    Timing.tick("done.");

    if (op.doDep) {
      System.err.print("Extracting Dependencies...");
      binaryTrainTrees.clear();
      Extractor<DependencyGrammar> dgExtractor =
          new MLEDependencyGrammarExtractor(op, wordIndex, tagIndex);
      // dgBLIPP = (DependencyGrammar) dgExtractor.extract(new
      // ConcatenationIterator(trainTreebank.iterator(),blippTreebank.iterator()),new
      // TransformTreeDependency(tlpParams,true));

      // DependencyGrammar dg1 = dgExtractor.extract(trainTreebank.iterator(), new
      // TransformTreeDependency(op.tlpParams, true));
      // dgBLIPP=(DependencyGrammar)dgExtractor.extract(blippTreebank.iterator(),new
      // TransformTreeDependency(tlpParams));

      // dg = (DependencyGrammar) dgExtractor.extract(new
      // ConcatenationIterator(trainTreebank.iterator(),blippTreebank.iterator()),new
      // TransformTreeDependency(tlpParams));
      // dg=new DependencyGrammarCombination(dg1,dgBLIPP,2);
      dg =
          dgExtractor.extract(
              binaryTrainTrees); // uses information whether the words are known or not, discards
      // unknown words
      Timing.tick("done.");
      // System.out.print("Extracting Unknown Word Model...");
      // UnknownWordModel uwm = (UnknownWordModel)uwmExtractor.extract(binaryTrainTrees);
      // Timing.tick("done.");
      System.out.print("Tuning Dependency Model...");
      dg.tune(binaryTestTrees);
      // System.out.println("TUNE DEPS: "+tuneDeps);
      Timing.tick("done.");
    }

    BinaryGrammar boundBG = bg;
    UnaryGrammar boundUG = ug;

    GrammarProjection gp = new NullGrammarProjection(bg, ug);

    // serialization
    if (serializeFile != null) {
      System.err.print("Serializing parser...");
      LexicalizedParser.saveParserDataToSerialized(
          new ParserData(lex, bg, ug, dg, stateIndex, wordIndex, tagIndex, op), serializeFile);
      Timing.tick("done.");
    }

    // test: pcfg-parse and output

    ExhaustivePCFGParser parser = null;
    if (op.doPCFG) {
      parser = new ExhaustivePCFGParser(boundBG, boundUG, lex, op, stateIndex, wordIndex, tagIndex);
    }

    ExhaustiveDependencyParser dparser =
        ((op.doDep && !op.testOptions.useFastFactored)
            ? new ExhaustiveDependencyParser(dg, lex, op, wordIndex, tagIndex)
            : null);

    Scorer scorer =
        (op.doPCFG ? new TwinScorer(new ProjectionScorer(parser, gp, op), dparser) : null);
    // Scorer scorer = parser;
    BiLexPCFGParser bparser = null;
    if (op.doPCFG && op.doDep) {
      bparser =
          (op.testOptions.useN5)
              ? new BiLexPCFGParser.N5BiLexPCFGParser(
                  scorer, parser, dparser, bg, ug, dg, lex, op, gp, stateIndex, wordIndex, tagIndex)
              : new BiLexPCFGParser(
                  scorer,
                  parser,
                  dparser,
                  bg,
                  ug,
                  dg,
                  lex,
                  op,
                  gp,
                  stateIndex,
                  wordIndex,
                  tagIndex);
    }

    Evalb pcfgPE = new Evalb("pcfg  PE", true);
    Evalb comboPE = new Evalb("combo PE", true);
    AbstractEval pcfgCB = new Evalb.CBEval("pcfg  CB", true);

    AbstractEval pcfgTE = new TaggingEval("pcfg  TE");
    AbstractEval comboTE = new TaggingEval("combo TE");
    AbstractEval pcfgTEnoPunct = new TaggingEval("pcfg nopunct TE");
    AbstractEval comboTEnoPunct = new TaggingEval("combo nopunct TE");
    AbstractEval depTE = new TaggingEval("depnd TE");

    AbstractEval depDE =
        new UnlabeledAttachmentEval("depnd DE", true, null, tlp.punctuationWordRejectFilter());
    AbstractEval comboDE =
        new UnlabeledAttachmentEval("combo DE", true, null, tlp.punctuationWordRejectFilter());

    if (op.testOptions.evalb) {
      EvalbFormatWriter.initEVALBfiles(op.tlpParams);
    }

    // int[] countByLength = new int[op.testOptions.maxLength+1];

    // Use a reflection ruse, so one can run this without needing the
    // tagger.  Using a function rather than a MaxentTagger means we
    // can distribute a version of the parser that doesn't include the
    // entire tagger.
    Function<List<? extends HasWord>, ArrayList<TaggedWord>> tagger = null;
    if (op.testOptions.preTag) {
      try {
        Class[] argsClass = {String.class};
        Object[] arguments = new Object[] {op.testOptions.taggerSerializedFile};
        tagger =
            (Function<List<? extends HasWord>, ArrayList<TaggedWord>>)
                Class.forName("edu.stanford.nlp.tagger.maxent.MaxentTagger")
                    .getConstructor(argsClass)
                    .newInstance(arguments);
      } catch (Exception e) {
        System.err.println(e);
        System.err.println("Warning: No pretagging of sentences will be done.");
      }
    }

    for (int tNum = 0, ttSize = testTreebank.size(); tNum < ttSize; tNum++) {
      Tree tree = testTreebank.get(tNum);
      int testTreeLen = tree.yield().size();
      if (testTreeLen > op.testOptions.maxLength) {
        continue;
      }
      Tree binaryTree = binaryTestTrees.get(tNum);
      // countByLength[testTreeLen]++;
      System.out.println("-------------------------------------");
      System.out.println("Number: " + (tNum + 1));
      System.out.println("Length: " + testTreeLen);

      // tree.pennPrint(pw);
      // System.out.println("XXXX The binary tree is");
      // binaryTree.pennPrint(pw);
      // System.out.println("Here are the tags in the lexicon:");
      // System.out.println(lex.showTags());
      // System.out.println("Here's the tagnumberer:");
      // System.out.println(Numberer.getGlobalNumberer("tags").toString());

      long timeMil1 = System.currentTimeMillis();
      Timing.tick("Starting parse.");
      if (op.doPCFG) {
        // System.err.println(op.testOptions.forceTags);
        if (op.testOptions.forceTags) {
          if (tagger != null) {
            // System.out.println("Using a tagger to set tags");
            // System.out.println("Tagged sentence as: " +
            // tagger.processSentence(cutLast(wordify(binaryTree.yield()))).toString(false));
            parser.parse(addLast(tagger.apply(cutLast(wordify(binaryTree.yield())))));
          } else {
            // System.out.println("Forcing tags to match input.");
            parser.parse(cleanTags(binaryTree.taggedYield(), tlp));
          }
        } else {
          // System.out.println("XXXX Parsing " + binaryTree.yield());
          parser.parse(binaryTree.yieldHasWord());
        }
        // Timing.tick("Done with pcfg phase.");
      }
      if (op.doDep) {
        dparser.parse(binaryTree.yieldHasWord());
        // Timing.tick("Done with dependency phase.");
      }
      boolean bothPassed = false;
      if (op.doPCFG && op.doDep) {
        bothPassed = bparser.parse(binaryTree.yieldHasWord());
        // Timing.tick("Done with combination phase.");
      }
      long timeMil2 = System.currentTimeMillis();
      long elapsed = timeMil2 - timeMil1;
      System.err.println("Time: " + ((int) (elapsed / 100)) / 10.00 + " sec.");
      // System.out.println("PCFG Best Parse:");
      Tree tree2b = null;
      Tree tree2 = null;
      // System.out.println("Got full best parse...");
      if (op.doPCFG) {
        tree2b = parser.getBestParse();
        tree2 = debinarizer.transformTree(tree2b);
      }
      // System.out.println("Debinarized parse...");
      // tree2.pennPrint();
      // System.out.println("DepG Best Parse:");
      Tree tree3 = null;
      Tree tree3db = null;
      if (op.doDep) {
        tree3 = dparser.getBestParse();
        // was: but wrong Tree tree3db = debinarizer.transformTree(tree2);
        tree3db = debinarizer.transformTree(tree3);
        tree3.pennPrint(pw);
      }
      // tree.pennPrint();
      // ((Tree)binaryTrainTrees.get(tNum)).pennPrint();
      // System.out.println("Combo Best Parse:");
      Tree tree4 = null;
      if (op.doPCFG && op.doDep) {
        try {
          tree4 = bparser.getBestParse();
          if (tree4 == null) {
            tree4 = tree2b;
          }
        } catch (NullPointerException e) {
          System.err.println("Blocked, using PCFG parse!");
          tree4 = tree2b;
        }
      }
      if (op.doPCFG && !bothPassed) {
        tree4 = tree2b;
      }
      // tree4.pennPrint();
      if (op.doDep) {
        depDE.evaluate(tree3, binaryTree, pw);
        depTE.evaluate(tree3db, tree, pw);
      }
      TreeTransformer tc = op.tlpParams.collinizer();
      TreeTransformer tcEvalb = op.tlpParams.collinizerEvalb();
      if (op.doPCFG) {
        // System.out.println("XXXX Best PCFG was: ");
        // tree2.pennPrint();
        // System.out.println("XXXX Transformed best PCFG is: ");
        // tc.transformTree(tree2).pennPrint();
        // System.out.println("True Best Parse:");
        // tree.pennPrint();
        // tc.transformTree(tree).pennPrint();
        pcfgPE.evaluate(tc.transformTree(tree2), tc.transformTree(tree), pw);
        pcfgCB.evaluate(tc.transformTree(tree2), tc.transformTree(tree), pw);
        Tree tree4b = null;
        if (op.doDep) {
          comboDE.evaluate((bothPassed ? tree4 : tree3), binaryTree, pw);
          tree4b = tree4;
          tree4 = debinarizer.transformTree(tree4);
          if (op.nodePrune) {
            NodePruner np = new NodePruner(parser, debinarizer);
            tree4 = np.prune(tree4);
          }
          // tree4.pennPrint();
          comboPE.evaluate(tc.transformTree(tree4), tc.transformTree(tree), pw);
        }
        // pcfgTE.evaluate(tree2, tree);
        pcfgTE.evaluate(tcEvalb.transformTree(tree2), tcEvalb.transformTree(tree), pw);
        pcfgTEnoPunct.evaluate(tc.transformTree(tree2), tc.transformTree(tree), pw);

        if (op.doDep) {
          comboTE.evaluate(tcEvalb.transformTree(tree4), tcEvalb.transformTree(tree), pw);
          comboTEnoPunct.evaluate(tc.transformTree(tree4), tc.transformTree(tree), pw);
        }
        System.out.println("PCFG only: " + parser.scoreBinarizedTree(tree2b, 0));

        // tc.transformTree(tree2).pennPrint();
        tree2.pennPrint(pw);

        if (op.doDep) {
          System.out.println("Combo: " + parser.scoreBinarizedTree(tree4b, 0));
          // tc.transformTree(tree4).pennPrint(pw);
          tree4.pennPrint(pw);
        }
        System.out.println("Correct:" + parser.scoreBinarizedTree(binaryTree, 0));
        /*
        if (parser.scoreBinarizedTree(tree2b,true) < parser.scoreBinarizedTree(binaryTree,true)) {
          System.out.println("SCORE INVERSION");
          parser.validateBinarizedTree(binaryTree,0);
        }
        */
        tree.pennPrint(pw);
      } // end if doPCFG

      if (op.testOptions.evalb) {
        if (op.doPCFG && op.doDep) {
          EvalbFormatWriter.writeEVALBline(
              tcEvalb.transformTree(tree), tcEvalb.transformTree(tree4));
        } else if (op.doPCFG) {
          EvalbFormatWriter.writeEVALBline(
              tcEvalb.transformTree(tree), tcEvalb.transformTree(tree2));
        } else if (op.doDep) {
          EvalbFormatWriter.writeEVALBline(
              tcEvalb.transformTree(tree), tcEvalb.transformTree(tree3db));
        }
      }
    } // end for each tree in test treebank

    if (op.testOptions.evalb) {
      EvalbFormatWriter.closeEVALBfiles();
    }

    // op.testOptions.display();
    if (op.doPCFG) {
      pcfgPE.display(false, pw);
      System.out.println("Grammar size: " + stateIndex.size());
      pcfgCB.display(false, pw);
      if (op.doDep) {
        comboPE.display(false, pw);
      }
      pcfgTE.display(false, pw);
      pcfgTEnoPunct.display(false, pw);
      if (op.doDep) {
        comboTE.display(false, pw);
        comboTEnoPunct.display(false, pw);
      }
    }
    if (op.doDep) {
      depTE.display(false, pw);
      depDE.display(false, pw);
    }
    if (op.doPCFG && op.doDep) {
      comboDE.display(false, pw);
    }
    // pcfgPE.printGoodBad();
  }
Пример #8
0
  /**
   * parse sentence and generate .trees file
   *
   * @param en
   * @param align
   * @param out
   */
  public static void parse(String en, String align, String out, boolean verbose) {

    // use alignments?
    boolean use_alignments = true;
    if (align.startsWith("no_align")) {
      use_alignments = false;
      System.err.println("Not using alignments.");
    } else {
      System.err.println("Using alignments from " + align);
    }

    // setup stanfordparser
    String grammar = "edu/stanford/nlp/models/lexparser/englishPCFG.ser.gz";
    String[] options = {"-outputFormat", "wordsAndTags, typedDependencies"};
    LexicalizedParser lp = LexicalizedParser.loadModel(grammar, options);
    TreebankLanguagePack tlp = lp.getOp().langpack();
    java.util.function.Predicate<java.lang.String> punctuationFilter = x -> true;

    GrammaticalStructureFactory gsf =
        new edu.stanford.nlp.trees.EnglishGrammaticalStructureFactory(punctuationFilter);

    // read document
    Iterable<List<? extends HasWord>> sentences;
    Reader r = new Reader(en);
    String line = null;
    List<List<? extends HasWord>> tmp = new ArrayList<List<? extends HasWord>>();
    while ((line = r.getNext()) != null) {
      Tokenizer<? extends HasWord> token =
          tlp.getTokenizerFactory().getTokenizer(new StringReader(line));
      List<? extends HasWord> sentence = token.tokenize();
      tmp.add(sentence);
    }
    sentences = tmp;

    // set up alignment file reader
    Reader alignment = new Reader();
    if (use_alignments) {
      alignment = new Reader(align);
    }

    // set up tree file writer
    Writer treeWriter = new Writer(out);

    // parse
    long start = System.currentTimeMillis();
    // System.err.print("Parsing sentences ");
    int sentID = 0;
    for (List<? extends HasWord> sentence : sentences) {
      Tree t = new Tree();
      // t.setSentID(++sentID);
      System.err.println("parse Sentence :" + sentence + "...");
      // System.err.print(".");
      System.err.println("-----------------------------------------------------------------------");
      edu.stanford.nlp.trees.Tree parse = lp.parse(sentence);
      // parse.pennPrint();

      // List for root node and lexical nodes
      List<Node> loneNodes = new LinkedList<Node>();
      List<Node> governingNodes = new LinkedList<Node>();

      // ROOT node
      Node root = new Node(true, true);
      root.setTag("ROOT");
      t.setRoot(root);
      loneNodes.add(root);
      governingNodes.add(root);

      // tagging

      int counter = 0;
      String surface = "";
      String tag = "";

      for (TaggedWord tw : parse.taggedYield()) {
        Node n = new Node();
        Node governingNode = new Node();
        n.setNodeID(++counter);
        surface = tw.value();
        tag = tw.tag();
        if (surface.startsWith("-LRB-")) {
          surface = "(";
        } else if (surface.startsWith("-RRB-")) {
          surface = ")";
          // } else if (surface.startsWith("-LSB-")){
          //    surface = "[";
          // } else if (surface.startsWith("-RSB-")){
          //    surface = "]";
          // } else if (surface.startsWith("-LCB-")){
          //    surface = "{";
          // } else if (surface.startsWith("-RCB-")){
          //    surface = "}";
        } else if (surface.startsWith("''")) {
          surface = "\"";
        }
        tag = tag.replaceAll("#", "-NUM-");
        surface = surface.replaceAll("&", "-AMP-");
        surface = surface.replaceAll("#", "-NUM-");
        surface = surface.replaceAll(">", "-GRE-");
        surface = surface.replaceAll("=", "-EQU-");
        n.setInitialLexicalIndex(counter);
        governingNode.setInitialLexicalIndex(counter);
        n.setSurface(surface);
        // System.out.print("("+tw.value()+" : ");
        n.setTag(tag);
        governingNode.setTag("_" + tag);
        governingNode.setLabel("_gov");
        // System.out.print(tw.tag()+")");
        loneNodes.add(n);
        governingNodes.add(governingNode);
        governingNode.setChild(n);
      }

      // System.out.println("");

      // t.setSentLength(t.getNodes().size() - 1);
      // List<Node> loneNodes = new LinkedList<Node>();
      Node[] nodes = new Node[2000];
      // labeling
      int depIndex;
      int govIndex;
      String[] depInfo;
      String[] govInfo;
      GrammaticalStructure gs = gsf.newGrammaticalStructure(parse);
      List<TypedDependency> tdl = gs.typedDependencies(false);
      // List<TypedDependency> tdl = gs.typedDependenciesCCprocessed();
      for (TypedDependency td : tdl) {
        depIndex = td.dep().index();
        govIndex = td.gov().index();
        // System.out.println("Index1:"+depIndex);
        // System.out.println("Index2:"+govIndex);
        // if (nodes[depIndex] == null){
        //	System.out.println("Making node!");
        //	nodes[depIndex] = new Node();
        // }
        // if (nodes[govIndex] == null){
        //	System.out.println("Making node!");
        //	nodes[govIndex] = new Node();
        // }
        Node dep = loneNodes.get((depIndex));
        Node gov = governingNodes.get((govIndex));
        Node depcopy = governingNodes.get((depIndex));
        Node govcopy = loneNodes.get((govIndex));
        dep.setLabel(td.reln().toString());
        depcopy.setLabel(td.reln().toString());
        govcopy.setLabel("head");
        // System.out.println(td.toString());
        govInfo = td.gov().toString().split("/");
        depInfo = td.dep().toString().split("/");
        // System.out.println(td.gov().toString());
        // System.out.println(td.dep().toString());
        // dep.setSurface(depInfo[0]);
        // dep.setTag(depInfo[1]);
        gov.setChild(governingNodes.get(depIndex));
        governingNodes.get(depIndex).setParent(gov);
        // gov.setChild(dep);
        dep.setParent(governingNodes.get(depIndex));
      }
      // t.setRoot(nodes[0]);

      // Collapse tree to remove unneeded governing nodes:

      Node gov;
      Node dep;
      Node parent;
      List<Node> children;

      for (int i = 1; i < governingNodes.size(); i++) { // start with index 1 to skip root
        gov = governingNodes.get(i);
        dep = loneNodes.get(i);
        if (gov.getChildren().size() <= 1) {
          int k = 0;
          parent = gov.getParent();
          children = parent.getChildren();

          for (Node n : children) {
            if (n == gov) {
              gov.getParent().replaceChild(k, dep);
              dep.setParent(gov.getParent());
            }
            k++;
          }
        }
      }
      // Mark head nodes with appropriate label:
      int k = 0;
      for (Node n : loneNodes) {
        if (k != 0) {
          if (n.getLabel() == n.getParent().getLabel()) {
            n.setLabel("head");
          }
        } else {
          n.setLabel("null");
        }
        k++;
      }
      // Sort lexical children of each governing node in lexical order

      for (Node n : governingNodes) {
        n.sortChildrenByInitialIndex();
      }

      // combine with alignment
      if (use_alignments) {
        t.initialize(alignment.readNextAlign());
      } else {
        t.initializeUnaligned();
      }

      // write tree to file
      treeWriter.write(t);

      // print tree to console

      System.out.println(t.toSentence());
      if (verbose) {
        System.err.println(t.toString());
        // t.recursivePrint();
      }
      System.err.println("#######################################################################");
    }
    long stop = System.currentTimeMillis();
    System.err.println("...done! [" + (stop - start) / 1000 + " sec].");

    treeWriter.close();
  }
Пример #9
0
 protected List<IntTaggedWord> treeToEvents(Tree tree) {
   List<TaggedWord> taggedWords = tree.taggedYield();
   return listToEvents(taggedWords);
 }
 @Override
 public void train(Tree tree) {
   train(tree.taggedYield());
 }