Beispiel #1
0
        private void TestOnTreebank(LexicalizedParser pd, ITreebankLangParserParams tlpParams, Treebank testTreebank, string treebankRoot, IIndex <string> stateIndex)
        {
            Timing.StartTime();
            ITreeTransformer annotator = new TreeAnnotator(tlpParams.HeadFinder(), tlpParams, op);

            // CDM: Aug 2004: With new implementation of treebank split categories,
            // I've hardwired this to load English ones.  Otherwise need training data.
            // op.trainOptions.splitters = new HashSet(Arrays.asList(op.tlpParams.splitters()));
            op.trainOptions.splitters       = ParentAnnotationStats.GetEnglishSplitCategories(treebankRoot);
            op.trainOptions.sisterSplitters = Generics.NewHashSet(Arrays.AsList(op.tlpParams.SisterSplitters()));
            foreach (Tree goldTree in testTreebank)
            {
                goldTree = annotator.TransformTree(goldTree);
                //      System.out.println();
                //      System.out.println("Checking tree: " + goldTree);
                foreach (Tree localTree in goldTree)
                {
                    // now try to use the grammar to score this local tree
                    if (localTree.IsLeaf() || localTree.IsPreTerminal() || localTree.Children().Length < 2)
                    {
                        continue;
                    }
                    System.Console.Out.WriteLine(LocalTreeToRule(localTree));
                    double score = ComputeLocalTreeScore(localTree, stateIndex, pd);
                    if (score == double.NegativeInfinity)
                    {
                    }
                    //          System.out.println(localTreeToRule(localTree));
                    System.Console.Out.WriteLine("score: " + score);
                }
            }
        }
 public TreebankAnnotator(Options op, string treebankRoot)
 {
     //    op.tlpParams = new EnglishTreebankParserParams();
     // CDM: Aug 2004: With new implementation of treebank split categories,
     // I've hardwired this to load English ones.  Otherwise need training data.
     // op.trainOptions.splitters = Generics.newHashSet(Arrays.asList(op.tlpParams.splitters()));
     op.trainOptions.splitters       = ParentAnnotationStats.GetEnglishSplitCategories(treebankRoot);
     op.trainOptions.sisterSplitters = Generics.NewHashSet(Arrays.AsList(op.tlpParams.SisterSplitters()));
     op.SetOptions("-acl03pcfg", "-cnf");
     treeTransformer = new TreeAnnotatorAndBinarizer(op.tlpParams, op.forceCNF, !op.trainOptions.OutsideFactor(), true, op);
     //    BinarizerFactory.TreeAnnotator.setTreebankLang(op.tlpParams);
     treeUnTransformer = new Debinarizer(op.forceCNF);
     collinizer        = op.tlpParams.Collinizer();
     this.op           = op;
 }
Beispiel #3
0
        private static Edu.Stanford.Nlp.Parser.Lexparser.ChineseLexiconAndWordSegmenter GetSegmenterDataFromTreebank(Treebank trainTreebank, Options op, IIndex <string> wordIndex, IIndex <string> tagIndex)
        {
            System.Console.Out.WriteLine("Currently " + new DateTime());
            //    printOptions(true, op);
            Timing.StartTime();
            // setup tree transforms
            ITreebankLangParserParams tlpParams = op.tlpParams;

            if (op.testOptions.verbose)
            {
                System.Console.Out.Write("Training ");
                System.Console.Out.WriteLine(trainTreebank.TextualSummary());
            }
            System.Console.Out.Write("Binarizing trees...");
            TreeAnnotatorAndBinarizer binarizer;

            // initialized below
            if (!op.trainOptions.leftToRight)
            {
                binarizer = new TreeAnnotatorAndBinarizer(tlpParams, op.forceCNF, !op.trainOptions.OutsideFactor(), true, op);
            }
            else
            {
                binarizer = new TreeAnnotatorAndBinarizer(tlpParams.HeadFinder(), new LeftHeadFinder(), tlpParams, op.forceCNF, !op.trainOptions.OutsideFactor(), true, op);
            }
            CollinsPuncTransformer collinsPuncTransformer = null;

            if (op.trainOptions.collinsPunc)
            {
                collinsPuncTransformer = new CollinsPuncTransformer(tlpParams.TreebankLanguagePack());
            }
            IList <Tree> binaryTrainTrees = new List <Tree>();

            // List<Tree> binaryTuneTrees = new ArrayList<Tree>();
            if (op.trainOptions.selectiveSplit)
            {
                op.trainOptions.splitters = ParentAnnotationStats.GetSplitCategories(trainTreebank, true, 0, op.trainOptions.selectiveSplitCutOff, op.trainOptions.tagSelectiveSplitCutOff, tlpParams.TreebankLanguagePack());
                if (op.testOptions.verbose)
                {
                    log.Info("Parent split categories: " + op.trainOptions.splitters);
                }
            }
            if (op.trainOptions.selectivePostSplit)
            {
                ITreeTransformer myTransformer = new TreeAnnotator(tlpParams.HeadFinder(), tlpParams, op);
                Treebank         annotatedTB   = trainTreebank.Transform(myTransformer);
                op.trainOptions.postSplitters = ParentAnnotationStats.GetSplitCategories(annotatedTB, true, 0, op.trainOptions.selectivePostSplitCutOff, op.trainOptions.tagSelectivePostSplitCutOff, tlpParams.TreebankLanguagePack());
                if (op.testOptions.verbose)
                {
                    log.Info("Parent post annotation split categories: " + op.trainOptions.postSplitters);
                }
            }
            if (op.trainOptions.hSelSplit)
            {
                binarizer.SetDoSelectiveSplit(false);
                foreach (Tree tree in trainTreebank)
                {
                    if (op.trainOptions.collinsPunc)
                    {
                        tree = collinsPuncTransformer.TransformTree(tree);
                    }
                    tree = binarizer.TransformTree(tree);
                }
                binarizer.SetDoSelectiveSplit(true);
            }
            foreach (Tree tree_1 in trainTreebank)
            {
                if (op.trainOptions.collinsPunc)
                {
                    tree_1 = collinsPuncTransformer.TransformTree(tree_1);
                }
                tree_1 = binarizer.TransformTree(tree_1);
                binaryTrainTrees.Add(tree_1);
            }
            Timing.Tick("done.");
            if (op.testOptions.verbose)
            {
                binarizer.DumpStats();
            }
            System.Console.Out.Write("Extracting Lexicon...");
            Edu.Stanford.Nlp.Parser.Lexparser.ChineseLexiconAndWordSegmenter clex = (Edu.Stanford.Nlp.Parser.Lexparser.ChineseLexiconAndWordSegmenter)op.tlpParams.Lex(op, wordIndex, tagIndex);
            clex.InitializeTraining(binaryTrainTrees.Count);
            clex.Train(binaryTrainTrees);
            clex.FinishTraining();
            Timing.Tick("done.");
            return(clex);
        }
Beispiel #4
0
        /// <returns>A Triple of binaryTrainTreebank, binarySecondaryTreebank, binaryTuneTreebank.</returns>
        public static Triple <Treebank, Treebank, Treebank> GetAnnotatedBinaryTreebankFromTreebank(Treebank trainTreebank, Treebank secondaryTreebank, Treebank tuneTreebank, Options op)
        {
            // setup tree transforms
            ITreebankLangParserParams tlpParams = op.tlpParams;
            ITreebankLanguagePack     tlp       = tlpParams.TreebankLanguagePack();

            if (op.testOptions.verbose)
            {
                PrintWriter pwErr = tlpParams.Pw(System.Console.Error);
                pwErr.Print("Training ");
                pwErr.Println(trainTreebank.TextualSummary(tlp));
                if (secondaryTreebank != null)
                {
                    pwErr.Print("Secondary training ");
                    pwErr.Println(secondaryTreebank.TextualSummary(tlp));
                }
            }
            CompositeTreeTransformer trainTransformer = new CompositeTreeTransformer();

            if (op.trainOptions.preTransformer != null)
            {
                trainTransformer.AddTransformer(op.trainOptions.preTransformer);
            }
            if (op.trainOptions.collinsPunc)
            {
                CollinsPuncTransformer collinsPuncTransformer = new CollinsPuncTransformer(tlp);
                trainTransformer.AddTransformer(collinsPuncTransformer);
            }
            log.Info("Binarizing trees...");
            Edu.Stanford.Nlp.Parser.Lexparser.TreeAnnotatorAndBinarizer binarizer;
            if (!op.trainOptions.leftToRight)
            {
                binarizer = new Edu.Stanford.Nlp.Parser.Lexparser.TreeAnnotatorAndBinarizer(tlpParams, op.forceCNF, !op.trainOptions.OutsideFactor(), !op.trainOptions.predictSplits, op);
            }
            else
            {
                binarizer = new Edu.Stanford.Nlp.Parser.Lexparser.TreeAnnotatorAndBinarizer(tlpParams.HeadFinder(), new LeftHeadFinder(), tlpParams, op.forceCNF, !op.trainOptions.OutsideFactor(), !op.trainOptions.predictSplits, op);
            }
            trainTransformer.AddTransformer(binarizer);
            if (op.wordFunction != null)
            {
                ITreeTransformer wordFunctionTransformer = new TreeLeafLabelTransformer(op.wordFunction);
                trainTransformer.AddTransformer(wordFunctionTransformer);
            }
            Treebank wholeTreebank;

            if (secondaryTreebank == null)
            {
                wholeTreebank = trainTreebank;
            }
            else
            {
                wholeTreebank = new CompositeTreebank(trainTreebank, secondaryTreebank);
            }
            if (op.trainOptions.selectiveSplit)
            {
                op.trainOptions.splitters = ParentAnnotationStats.GetSplitCategories(wholeTreebank, op.trainOptions.tagSelectiveSplit, 0, op.trainOptions.selectiveSplitCutOff, op.trainOptions.tagSelectiveSplitCutOff, tlp);
                RemoveDeleteSplittersFromSplitters(tlp, op);
                if (op.testOptions.verbose)
                {
                    IList <string> list = new List <string>(op.trainOptions.splitters);
                    list.Sort();
                    log.Info("Parent split categories: " + list);
                }
            }
            if (op.trainOptions.selectivePostSplit)
            {
                // Do all the transformations once just to learn selective splits on annotated categories
                ITreeTransformer myTransformer = new TreeAnnotator(tlpParams.HeadFinder(), tlpParams, op);
                wholeTreebank = wholeTreebank.Transform(myTransformer);
                op.trainOptions.postSplitters = ParentAnnotationStats.GetSplitCategories(wholeTreebank, true, 0, op.trainOptions.selectivePostSplitCutOff, op.trainOptions.tagSelectivePostSplitCutOff, tlp);
                if (op.testOptions.verbose)
                {
                    log.Info("Parent post annotation split categories: " + op.trainOptions.postSplitters);
                }
            }
            if (op.trainOptions.hSelSplit)
            {
                // We run through all the trees once just to gather counts for hSelSplit!
                int ptt = op.trainOptions.printTreeTransformations;
                op.trainOptions.printTreeTransformations = 0;
                binarizer.SetDoSelectiveSplit(false);
                foreach (Tree tree in wholeTreebank)
                {
                    trainTransformer.TransformTree(tree);
                }
                binarizer.SetDoSelectiveSplit(true);
                op.trainOptions.printTreeTransformations = ptt;
            }
            // we've done all the setup now. here's where the train treebank is transformed.
            trainTreebank = trainTreebank.Transform(trainTransformer);
            if (secondaryTreebank != null)
            {
                secondaryTreebank = secondaryTreebank.Transform(trainTransformer);
            }
            if (op.trainOptions.printAnnotatedStateCounts)
            {
                binarizer.PrintStateCounts();
            }
            if (op.trainOptions.printAnnotatedRuleCounts)
            {
                binarizer.PrintRuleCounts();
            }
            if (tuneTreebank != null)
            {
                tuneTreebank = tuneTreebank.Transform(trainTransformer);
            }
            if (op.testOptions.verbose)
            {
                binarizer.DumpStats();
            }
            return(new Triple <Treebank, Treebank, Treebank>(trainTreebank, secondaryTreebank, tuneTreebank));
        }
Beispiel #5
0
        /* some documentation for Roger's convenience
         * {pcfg,dep,combo}{PE,DE,TE} are precision/dep/tagging evals for the models
         *
         * parser is the PCFG parser
         * dparser is the dependency parser
         * bparser is the combining parser
         *
         * during testing:
         * tree is the test tree (gold tree)
         * binaryTree is the gold tree binarized
         * tree2b is the best PCFG paser, binarized
         * tree2 is the best PCFG parse (debinarized)
         * tree3 is the dependency parse, binarized
         * tree3db is the dependency parser, debinarized
         * tree4 is the best combo parse, binarized and then debinarized
         * tree4b is the best combo parse, binarized
         */
        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.
            StringUtils.LogInvocationString(log, args);
            string path          = "/u/nlp/stuff/corpora/Treebank3/parsed/mrg/wsj";
            int    trainLow      = 200;
            int    trainHigh     = 2199;
            int    testLow       = 2200;
            int    testHigh      = 2219;
            string serializeFile = null;
            int    i             = 0;

            while (i < args.Length && args[i].StartsWith("-"))
            {
                if (Sharpen.Runtime.EqualsIgnoreCase(args[i], "-path") && (i + 1 < args.Length))
                {
                    path = args[i + 1];
                    i   += 2;
                }
                else
                {
                    if (Sharpen.Runtime.EqualsIgnoreCase(args[i], "-train") && (i + 2 < args.Length))
                    {
                        trainLow  = System.Convert.ToInt32(args[i + 1]);
                        trainHigh = System.Convert.ToInt32(args[i + 2]);
                        i        += 3;
                    }
                    else
                    {
                        if (Sharpen.Runtime.EqualsIgnoreCase(args[i], "-test") && (i + 2 < args.Length))
                        {
                            testLow  = System.Convert.ToInt32(args[i + 1]);
                            testHigh = System.Convert.ToInt32(args[i + 2]);
                            i       += 3;
                        }
                        else
                        {
                            if (Sharpen.Runtime.EqualsIgnoreCase(args[i], "-serialize") && (i + 1 < args.Length))
                            {
                                serializeFile = args[i + 1];
                                i            += 2;
                            }
                            else
                            {
                                if (Sharpen.Runtime.EqualsIgnoreCase(args[i], "-tLPP") && (i + 1 < args.Length))
                                {
                                    try
                                    {
                                        op.tlpParams = (ITreebankLangParserParams)System.Activator.CreateInstance(Sharpen.Runtime.GetType(args[i + 1]));
                                    }
                                    catch (TypeLoadException e)
                                    {
                                        log.Info("Class not found: " + args[i + 1]);
                                        throw new Exception(e);
                                    }
                                    catch (InstantiationException e)
                                    {
                                        log.Info("Couldn't instantiate: " + args[i + 1] + ": " + e.ToString());
                                        throw new Exception(e);
                                    }
                                    catch (MemberAccessException e)
                                    {
                                        log.Info("illegal access" + e);
                                        throw new Exception(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());
            ITreebankLanguagePack tlp = op.tlpParams.TreebankLanguagePack();

            op.trainOptions.sisterSplitters = Generics.NewHashSet(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();
            log.Info("Reading trees...");
            testTreebank.LoadPath(path, new NumberRangeFileFilter(testLow, testHigh, true));
            if (op.testOptions.increasingLength)
            {
                testTreebank.Sort(new TreeLengthComparator());
            }
            trainTreebank.LoadPath(path, new NumberRangeFileFilter(trainLow, trainHigh, true));
            Timing.Tick("done.");
            log.Info("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);
            }
            ITreeTransformer debinarizer      = new Debinarizer(op.forceCNF);
            IList <Tree>     binaryTrainTrees = new List <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)
                {
                    IList <string> deleted = new List <string>();
                    foreach (string del in op.trainOptions.deleteSplitters)
                    {
                        string baseDel    = tlp.BasicCategory(del);
                        bool   checkBasic = del.Equals(baseDel);
                        for (IEnumerator <string> it = op.trainOptions.splitters.GetEnumerator(); it.MoveNext();)
                        {
                            string elem     = it.Current;
                            string baseElem = tlp.BasicCategory(elem);
                            bool   delStr   = checkBasic && baseElem.Equals(baseDel) || elem.Equals(del);
                            if (delStr)
                            {
                                it.Remove();
                                deleted.Add(elem);
                            }
                        }
                    }
                    log.Info("Removed from vertical splitters: " + deleted);
                }
            }
            if (op.trainOptions.selectivePostSplit)
            {
                ITreeTransformer 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);
                foreach (Tree tree in trainTreebank)
                {
                    if (op.trainOptions.collinsPunc)
                    {
                        tree = collinsPuncTransformer.TransformTree(tree);
                    }
                    //tree.pennPrint(tlpParams.pw());
                    tree = binarizer.TransformTree(tree);
                }
                //binaryTrainTrees.add(tree);
                binarizer.SetDoSelectiveSplit(true);
            }
            foreach (Tree tree_1 in trainTreebank)
            {
                if (op.trainOptions.collinsPunc)
                {
                    tree_1 = collinsPuncTransformer.TransformTree(tree_1);
                }
                tree_1 = binarizer.TransformTree(tree_1);
                binaryTrainTrees.Add(tree_1);
            }
            if (op.testOptions.verbose)
            {
                binarizer.DumpStats();
            }
            IList <Tree> binaryTestTrees = new List <Tree>();

            foreach (Tree tree_2 in testTreebank)
            {
                if (op.trainOptions.collinsPunc)
                {
                    tree_2 = collinsPuncTransformer.TransformTree(tree_2);
                }
                tree_2 = binarizer.TransformTree(tree_2);
                binaryTestTrees.Add(tree_2);
            }
            Timing.Tick("done.");
            // binarization
            BinaryGrammar      bg = null;
            UnaryGrammar       ug = null;
            IDependencyGrammar dg = null;
            // DependencyGrammar dgBLIPP = null;
            ILexicon        lex        = null;
            IIndex <string> stateIndex = new HashIndex <string>();
            // extract grammars
            IExtractor <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)
            {
                log.Info("Extracting PCFG...");
                Pair <UnaryGrammar, BinaryGrammar> bgug = null;
                if (op.trainOptions.cheatPCFG)
                {
                    IList <Tree> allTrees = new List <Tree>(binaryTrainTrees);
                    Sharpen.Collections.AddAll(allTrees, binaryTestTrees);
                    bgug = bgExtractor.Extract(allTrees);
                }
                else
                {
                    bgug = bgExtractor.Extract(binaryTrainTrees);
                }
                bg = bgug.second;
                bg.SplitRules();
                ug = bgug.first;
                ug.PurgeRules();
                Timing.Tick("done.");
            }
            log.Info("Extracting Lexicon...");
            IIndex <string> wordIndex = new HashIndex <string>();
            IIndex <string> tagIndex  = new HashIndex <string>();

            lex = op.tlpParams.Lex(op, wordIndex, tagIndex);
            lex.InitializeTraining(binaryTrainTrees.Count);
            lex.Train(binaryTrainTrees);
            lex.FinishTraining();
            Timing.Tick("done.");
            if (op.doDep)
            {
                log.Info("Extracting Dependencies...");
                binaryTrainTrees.Clear();
                IExtractor <IDependencyGrammar> 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.Console.Out.Write("Tuning Dependency Model...");
                dg.Tune(binaryTestTrees);
                //System.out.println("TUNE DEPS: "+tuneDeps);
                Timing.Tick("done.");
            }
            BinaryGrammar      boundBG = bg;
            UnaryGrammar       boundUG = ug;
            IGrammarProjection gp      = new NullGrammarProjection(bg, ug);

            // serialization
            if (serializeFile != null)
            {
                log.Info("Serializing parser...");
                LexicalizedParser parser = new LexicalizedParser(lex, bg, ug, dg, stateIndex, wordIndex, tagIndex, op);
                parser.SaveParserToSerialized(serializeFile);
                Timing.Tick("done.");
            }
            // test: pcfg-parse and output
            ExhaustivePCFGParser parser_1 = null;

            if (op.doPCFG)
            {
                parser_1 = new ExhaustivePCFGParser(boundBG, boundUG, lex, op, stateIndex, wordIndex, tagIndex);
            }
            ExhaustiveDependencyParser dparser = ((op.doDep && !op.testOptions.useFastFactored) ? new ExhaustiveDependencyParser(dg, lex, op, wordIndex, tagIndex) : null);
            IScorer scorer = (op.doPCFG ? new TwinScorer(new ProjectionScorer(parser_1, gp, op), dparser) : null);
            //Scorer scorer = parser;
            BiLexPCFGParser bparser = null;

            if (op.doPCFG && op.doDep)
            {
                bparser = (op.testOptions.useN5) ? new BiLexPCFGParser.N5BiLexPCFGParser(scorer, parser_1, dparser, bg, ug, dg, lex, op, gp, stateIndex, wordIndex, tagIndex) : new BiLexPCFGParser(scorer, parser_1, 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.
            IFunction <IList <IHasWord>, List <TaggedWord> > tagger = null;

            if (op.testOptions.preTag)
            {
                try
                {
                    Type[]   argsClass = new Type[] { typeof(string) };
                    object[] arguments = new object[] { op.testOptions.taggerSerializedFile };
                    tagger = (IFunction <IList <IHasWord>, List <TaggedWord> >)Sharpen.Runtime.GetType("edu.stanford.nlp.tagger.maxent.MaxentTagger").GetConstructor(argsClass).NewInstance(arguments);
                }
                catch (Exception e)
                {
                    log.Info(e);
                    log.Info("Warning: No pretagging of sentences will be done.");
                }
            }
            for (int tNum = 0; tNum < ttSize; tNum++)
            {
                Tree tree        = testTreebank[tNum];
                int  testTreeLen = tree_2.Yield().Count;
                if (testTreeLen > op.testOptions.maxLength)
                {
                    continue;
                }
                Tree binaryTree = binaryTestTrees[tNum];
                // countByLength[testTreeLen]++;
                System.Console.Out.WriteLine("-------------------------------------");
                System.Console.Out.WriteLine("Number: " + (tNum + 1));
                System.Console.Out.WriteLine("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 = Runtime.CurrentTimeMillis();
                Timing.Tick("Starting parse.");
                if (op.doPCFG)
                {
                    //log.info(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_1.Parse(AddLast(tagger.Apply(CutLast(Wordify(binaryTree.Yield())))));
                        }
                        else
                        {
                            //System.out.println("Forcing tags to match input.");
                            parser_1.Parse(CleanTags(binaryTree.TaggedYield(), tlp));
                        }
                    }
                    else
                    {
                        // System.out.println("XXXX Parsing " + binaryTree.yield());
                        parser_1.Parse(binaryTree.YieldHasWord());
                    }
                }
                //Timing.tick("Done with pcfg phase.");
                if (op.doDep)
                {
                    dparser.Parse(binaryTree.YieldHasWord());
                }
                //Timing.tick("Done with dependency phase.");
                bool bothPassed = false;
                if (op.doPCFG && op.doDep)
                {
                    bothPassed = bparser.Parse(binaryTree.YieldHasWord());
                }
                //Timing.tick("Done with combination phase.");
                long timeMil2 = Runtime.CurrentTimeMillis();
                long elapsed  = timeMil2 - timeMil1;
                log.Info("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_1.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 (ArgumentNullException)
                    {
                        log.Info("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_2, pw);
                }
                ITreeTransformer tc      = op.tlpParams.Collinizer();
                ITreeTransformer 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_2), pw);
                    pcfgCB.Evaluate(tc.TransformTree(tree2), tc.TransformTree(tree_2), 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_1, debinarizer);
                            tree4 = np.Prune(tree4);
                        }
                        //tree4.pennPrint();
                        comboPE.Evaluate(tc.TransformTree(tree4), tc.TransformTree(tree_2), pw);
                    }
                    //pcfgTE.evaluate(tree2, tree);
                    pcfgTE.Evaluate(tcEvalb.TransformTree(tree2), tcEvalb.TransformTree(tree_2), pw);
                    pcfgTEnoPunct.Evaluate(tc.TransformTree(tree2), tc.TransformTree(tree_2), pw);
                    if (op.doDep)
                    {
                        comboTE.Evaluate(tcEvalb.TransformTree(tree4), tcEvalb.TransformTree(tree_2), pw);
                        comboTEnoPunct.Evaluate(tc.TransformTree(tree4), tc.TransformTree(tree_2), pw);
                    }
                    System.Console.Out.WriteLine("PCFG only: " + parser_1.ScoreBinarizedTree(tree2b, 0));
                    //tc.transformTree(tree2).pennPrint();
                    tree2.PennPrint(pw);
                    if (op.doDep)
                    {
                        System.Console.Out.WriteLine("Combo: " + parser_1.ScoreBinarizedTree(tree4b, 0));
                        // tc.transformTree(tree4).pennPrint(pw);
                        tree4.PennPrint(pw);
                    }
                    System.Console.Out.WriteLine("Correct:" + parser_1.ScoreBinarizedTree(binaryTree, 0));

                    /*
                     * if (parser.scoreBinarizedTree(tree2b,true) < parser.scoreBinarizedTree(binaryTree,true)) {
                     * System.out.println("SCORE INVERSION");
                     * parser.validateBinarizedTree(binaryTree,0);
                     * }
                     */
                    tree_2.PennPrint(pw);
                }
                // end if doPCFG
                if (op.testOptions.evalb)
                {
                    if (op.doPCFG && op.doDep)
                    {
                        EvalbFormatWriter.WriteEVALBline(tcEvalb.TransformTree(tree_2), tcEvalb.TransformTree(tree4));
                    }
                    else
                    {
                        if (op.doPCFG)
                        {
                            EvalbFormatWriter.WriteEVALBline(tcEvalb.TransformTree(tree_2), tcEvalb.TransformTree(tree2));
                        }
                        else
                        {
                            if (op.doDep)
                            {
                                EvalbFormatWriter.WriteEVALBline(tcEvalb.TransformTree(tree_2), 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.Console.Out.WriteLine("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);
            }
        }