上次（http://www.cnblogs.com/stGeekpower/p/3457746.html）主要是对应于javadoc写了下LexicalizedParser类main函数的功能，这次看下main函数的具体处理过程。main函数大概350行左右，主要完成的工作是：初始化变量（各种标志位）、解析传入的各种参数、根据传入的选项参数分步骤完成各种工作。
根据选项来做的工作按顺序主要包括：分词（必须最先处理）、初始化LexicalizedParser（读入或训练）、编码设置、测试、保存（如果需要的话）、解析输出结果。
具体解析的部分：对句子解析是通过LexicalizedParser对象生成的ParserQuery类的parse函数来完成，对文件的解析由ParseFiles类的parseFiles函数（最终也是调用ParserQuery类）完成。
一、初始化变量
这部分主要处理申明一些标志位，以及构建解析器需要的变量；
boolean train = false;//train or parse
boolean saveToSerializedFile = false;//是否序列化存储至文件
boolean saveToTextFile = false;//是否存储至文本文件
String serializedInputFileOrUrl = null;//序列化输入文件或者url
String textInputFileOrUrl = null;//文本输入文件或者url
String serializedOutputFileOrUrl = null;//序列化输出文件或者url
String textOutputFileOrUrl = null;//文本输入文件或者url
String treebankPath = null;//语法树路径
Treebank testTreebank = null;
Treebank tuneTreebank = null;
String testPath = null;
FileFilter testFilter = null;
String tunePath = null;
FileFilter tuneFilter = null;
FileFilter trainFilter = null;//训练过滤范围
String secondaryTreebankPath = null;
double secondaryTreebankWeight = 1.0;
FileFilter secondaryTrainFilter = null; // variables needed to process the files to be parsed
TokenizerFactory<? extends HasWord> tokenizerFactory = null; //分词工厂
String tokenizerOptions = null;//分词所需参数
String tokenizerFactoryClass = null;//分词所用类
String tokenizerMethod = null;//分词所用方法
boolean tokenized = false; // whether or not the input file has already been tokenized
Function<List<HasWord>, List<HasWord>> escaper = null; //转义
String tagDelimiter = null; //分隔符
String sentenceDelimiter = null;
String elementDelimiter = null;
二、解析传入的各种参数
这里处理用户传入的各种选项参数，存入在一种申明的变量中；
int argIndex = 0;
if (args.length < 1) {//参数数量为0，错误返回
System.err.println("Basic usage (see Javadoc for more): java edu.stanford.nlp.parser.lexparser" +
".LexicalizedParser parserFileOrUrl filename*");
return;
} Options op = new Options(); //处理参数的对象
List<String> optionArgs = new ArrayList<String>();
String encoding = null;
// while loop through option arguments,循环处理选项参数
while (argIndex < args.length && args[argIndex].charAt(0) == '-') {
if (args[argIndex].equalsIgnoreCase("-train") || args[argIndex].equalsIgnoreCase("-trainTreebank")) {//判断是否执行训练功能
train = true;
//处理训练时传入的参数信息，得到文件路径和过滤范围存至treebankDescription
Pair<String, FileFilter> treebankDescription = ArgUtils.getTreebankDescription(args, argIndex, "-test");
argIndex = argIndex + ArgUtils.numSubArgs(args, argIndex) + 1;
treebankPath = treebankDescription.first();
trainFilter = treebankDescription.second();
} else if (args[argIndex].equalsIgnoreCase("-train2")) {
// TODO: we could use the fully expressive -train options if
// we add some mechanism for returning leftover options from
// ArgUtils.getTreebankDescription
// train = true; // cdm july 2005: should require -train for this
int numSubArgs = ArgUtils.numSubArgs(args, argIndex);
argIndex++;
if (numSubArgs < 2) {
throw new RuntimeException("Error: -train2 <treebankPath> [<ranges>] <weight>.");
}
secondaryTreebankPath = args[argIndex++];
secondaryTrainFilter = (numSubArgs == 3) ? new NumberRangesFileFilter(args[argIndex++], true) : null;
secondaryTreebankWeight = Double.parseDouble(args[argIndex++]);
} else if (args[argIndex].equalsIgnoreCase("-tLPP") && (argIndex + 1 < args.length)) {
// 当使用除英文外的语言或者English Penn Treebank之外的Treebank时候需要指定TreebankLangParserParams，
// 该选项必须出现在其他的与语言相关的选项之前。不同的语言有不同的参数
try {
op.tlpParams = (TreebankLangParserParams) Class.forName(args[argIndex + 1]).newInstance();
} catch (ClassNotFoundException e) {
System.err.println("Class not found: " + args[argIndex + 1]);
throw new RuntimeException(e);
} catch (InstantiationException e) {
System.err.println("Couldn't instantiate: " + args[argIndex + 1] + ": " + e.toString());
throw new RuntimeException(e);
} catch (IllegalAccessException e) {
System.err.println("Illegal access" + e);
throw new RuntimeException(e);
}
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-encoding")) {//编码
// sets encoding for TreebankLangParserParams
// redone later to override any serialized parser one read in
encoding = args[argIndex + 1];
op.tlpParams.setInputEncoding(encoding);
op.tlpParams.setOutputEncoding(encoding);
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-tokenized")) {//是否已经分词
tokenized = true;
argIndex += 1;
} else if (args[argIndex].equalsIgnoreCase("-escaper")) {
try {
escaper = ReflectionLoading.loadByReflection(args[argIndex + 1]);
} catch (Exception e) {
System.err.println("Couldn't instantiate escaper " + args[argIndex + 1] + ": " + e);
}
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-tokenizerOptions")) {//指定TokenizerFactory类完成tokenization 所需要的参数信息
tokenizerOptions = args[argIndex + 1];
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-tokenizerFactory")) {//指定一个TokenizerFactory类来完成分词
tokenizerFactoryClass = args[argIndex + 1];
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-tokenizerMethod")) {//分词方法
tokenizerMethod = args[argIndex + 1];
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-sentences")) {//指定一个词语来划分句子边界,即分句根据
sentenceDelimiter = args[argIndex + 1];
if (sentenceDelimiter.equalsIgnoreCase("newline")) {
sentenceDelimiter = "\n";
}
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-parseInside")) {//解析的范围，可以是句，几句等等
elementDelimiter = args[argIndex + 1];
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-tagSeparator")) {//指明标注符号
tagDelimiter = args[argIndex + 1];
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-loadFromSerializedFile") ||
args[argIndex].equalsIgnoreCase("-model")) {
// load the parser from a binary serialized file
// the next argument must be the path to the parser file
serializedInputFileOrUrl = args[argIndex + 1];
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-loadFromTextFile")) {
// load the parser from declarative text file
// the next argument must be the path to the parser file
textInputFileOrUrl = args[argIndex + 1];
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-saveToSerializedFile")) {
saveToSerializedFile = true;
if (ArgUtils.numSubArgs(args, argIndex) < 1) {
System.err.println("Missing path: -saveToSerialized filename");
} else {
serializedOutputFileOrUrl = args[argIndex + 1];
}
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-saveToTextFile")) {
// save the parser to declarative text file
saveToTextFile = true;
textOutputFileOrUrl = args[argIndex + 1];
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-saveTrainTrees")) {
// save the training trees to a binary file
op.trainOptions.trainTreeFile = args[argIndex + 1];
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-treebank") ||
args[argIndex].equalsIgnoreCase("-testTreebank") ||
args[argIndex].equalsIgnoreCase("-test")) {//训练并测试，测试所需的参数
Pair<String, FileFilter> treebankDescription = ArgUtils.getTreebankDescription(args, argIndex, "-test");
argIndex = argIndex + ArgUtils.numSubArgs(args, argIndex) + 1;
testPath = treebankDescription.first();
testFilter = treebankDescription.second();
} else if (args[argIndex].equalsIgnoreCase("-tune")) {
Pair<String, FileFilter> treebankDescription = ArgUtils.getTreebankDescription(args, argIndex, "-tune");
argIndex = argIndex + ArgUtils.numSubArgs(args, argIndex) + 1;
tunePath = treebankDescription.first();
tuneFilter = treebankDescription.second();
} else {
int oldIndex = argIndex;
argIndex = op.setOptionOrWarn(args, argIndex);
for (int i = oldIndex; i < argIndex; i++) {
optionArgs.add(args[i]);
}
}
} // end while loop through arguments
三、分词处理
句法分析的前提是句子已经被正确分词，这里即完成分词工作，当然分词我们可以选用自己合适的分词器；
// set up tokenizerFactory with options if provided
if (tokenizerFactoryClass != null || tokenizerOptions != null) {
try {//分词工厂类、分词方法由参数指定，若不指定，默认PTBTokenizer
if (tokenizerFactoryClass != null) {
Class<TokenizerFactory<? extends HasWord>> clazz = ErasureUtils.uncheckedCast(Class.forName
(tokenizerFactoryClass));
Method factoryMethod;
if (tokenizerOptions != null) {
factoryMethod = clazz.getMethod(tokenizerMethod != null ? tokenizerMethod :
"newWordTokenizerFactory", String.class);
tokenizerFactory = ErasureUtils.uncheckedCast(factoryMethod.invoke(null, tokenizerOptions));
} else {
factoryMethod = clazz.getMethod(tokenizerMethod != null ? tokenizerMethod :
"newTokenizerFactory");
tokenizerFactory = ErasureUtils.uncheckedCast(factoryMethod.invoke(null));
}
} else {
// have options but no tokenizer factory; default to PTB
tokenizerFactory = PTBTokenizer.PTBTokenizerFactory.newWordTokenizerFactory(tokenizerOptions);
}
} catch (IllegalAccessException e) {
System.err.println("Couldn't instantiate TokenizerFactory " + tokenizerFactoryClass + " with options " +
"" + tokenizerOptions);
throw new RuntimeException(e);
} catch (NoSuchMethodException e) {
System.err.println("Couldn't instantiate TokenizerFactory " + tokenizerFactoryClass + " with options " +
"" + tokenizerOptions);
throw new RuntimeException(e);
} catch (ClassNotFoundException e) {
System.err.println("Couldn't instantiate TokenizerFactory " + tokenizerFactoryClass + " with options " +
"" + tokenizerOptions);
throw new RuntimeException(e);
} catch (InvocationTargetException e) {
System.err.println("Couldn't instantiate TokenizerFactory " + tokenizerFactoryClass + " with options " +
"" + tokenizerOptions);
throw new RuntimeException(e);
}
四、初始化LexicalizedParser
初始化LexicalizedParser有三种方式，分别是：根据数据训练一个，从文本文件读入，从序列化文件读入；
if (tuneFilter != null || tunePath != null) {//处理tune treebank
if (tunePath == null) {
if (treebankPath == null) {
throw new RuntimeException("No tune treebank path specified...");
} else {
System.err.println("No tune treebank path specified. Using train path: \"" + treebankPath + '\"');
tunePath = treebankPath;
}
}
tuneTreebank = op.tlpParams.testMemoryTreebank();
tuneTreebank.loadPath(tunePath, tuneFilter);
}
if (!train && op.testOptions.verbose) {
StringUtils.printErrInvocationString("LexicalizedParser", args);
}
edu.stanford.nlp.parser.lexparser.LexicalizedParser lp; // always initialized in next if-then-else block
if (train) {
StringUtils.printErrInvocationString("LexicalizedParser", args);
// so we train a parser using the treebank
GrammarCompactor compactor = null;
if (op.trainOptions.compactGrammar() == 3) {
compactor = new ExactGrammarCompactor(op, false, false);
}
Treebank trainTreebank = makeTreebank(treebankPath, op, trainFilter);
Treebank secondaryTrainTreebank = null;
if (secondaryTreebankPath != null) {
secondaryTrainTreebank = makeSecondaryTreebank(secondaryTreebankPath, op, secondaryTrainFilter);
}
List<List<TaggedWord>> extraTaggedWords = null;
if (op.trainOptions.taggedFiles != null) {
extraTaggedWords = new ArrayList<List<TaggedWord>>();
List<TaggedFileRecord> fileRecords = TaggedFileRecord.createRecords(new Properties(),
op.trainOptions.taggedFiles);
for (TaggedFileRecord record : fileRecords) {
for (List<TaggedWord> sentence : record.reader()) {
extraTaggedWords.add(sentence);
}
}
}
//执行训练方法时对lp的初始化，根据标注数据训练出lp
lp = getParserFromTreebank(trainTreebank, secondaryTrainTreebank, secondaryTreebankWeight, compactor, op,
tuneTreebank, extraTaggedWords);
} else if (textInputFileOrUrl != null) {
// so we load the parser from a text grammar file,直接从文本文件中读入lp
lp = getParserFromTextFile(textInputFileOrUrl, op);
} else {
// so we load a serialized parser,从序列化保存的文件中读入lp
if (serializedInputFileOrUrl == null && argIndex < args.length) {
// the next argument must be the path to the serialized parser
serializedInputFileOrUrl = args[argIndex];
argIndex++;
}
if (serializedInputFileOrUrl == null) {
System.err.println("No grammar specified, exiting...");
return;
}
String[] extraArgs = new String[optionArgs.size()];
extraArgs = optionArgs.toArray(extraArgs);
try {
lp = loadModel(serializedInputFileOrUrl, op, extraArgs);
op = lp.op;
} catch (IllegalArgumentException e) {
System.err.println("Error loading parser, exiting...");
throw e;
}
}
五、控制编码
// the following has to go after reading parser to make sure
// op and tlpParams are the same for train and test
// THIS IS BUTT UGLY BUT IT STOPS USER SPECIFIED ENCODING BEING
// OVERWRITTEN BY ONE SPECIFIED IN SERIALIZED PARSER
if (encoding != null) {
op.tlpParams.setInputEncoding(encoding);
op.tlpParams.setOutputEncoding(encoding);
}
六、测试数据设置
if (testFilter != null || testPath != null) {
if (testPath == null) {
if (treebankPath == null) {
throw new RuntimeException("No test treebank path specified...");
} else {
System.err.println("No test treebank path specified. Using train path: \"" + treebankPath + '\"');
testPath = treebankPath;
}
}
testTreebank = op.tlpParams.testMemoryTreebank();
testTreebank.loadPath(testPath, testFilter);
}
七、需要的话将训练生成的解析器保存
op.trainOptions.sisterSplitters = Generics.newHashSet(Arrays.asList(op.tlpParams.sisterSplitters()));
// at this point we should be sure that op.tlpParams is
// set appropriately (from command line, or from grammar file),
// and will never change again. -- Roger
// Now what do we do with the parser we've made
if (saveToTextFile) {
// save the parser to textGrammar format
if (textOutputFileOrUrl != null) {
lp.saveParserToTextFile(textOutputFileOrUrl);
} else {
System.err.println("Usage: must specify a text grammar output path");
}
}
if (saveToSerializedFile) {
if (serializedOutputFileOrUrl != null) {
lp.saveParserToSerialized(serializedOutputFileOrUrl);
} else if (textOutputFileOrUrl == null && testTreebank == null) {
// no saving/parsing request has been specified
System.err.println("usage: " + "java edu.stanford.nlp.parser.lexparser.LexicalizedParser " + "-train " +
"trainFilesPath [fileRange] -saveToSerializedFile serializedParserFilename");
}
}
八、训练或者指定输入参数时，输出一些信息
if (op.testOptions.verbose || train) {
// Tell the user a little or a lot about what we have made
// get lexicon size separately as it may have its own prints in it....
String lexNumRules = lp.lex != null ? Integer.toString(lp.lex.numRules()) : "";
System.err.println("Grammar\tStates\tTags\tWords\tUnaryR\tBinaryR\tTaggings");
System.err.println("Grammar\t" +
lp.stateIndex.size() + '\t' +
lp.tagIndex.size() + '\t' +
lp.wordIndex.size() + '\t' +
(lp.ug != null ? lp.ug.numRules() : "") + '\t' +
(lp.bg != null ? lp.bg.numRules() : "") + '\t' +
lexNumRules);
System.err.println("ParserPack is " + op.tlpParams.getClass().getName());
System.err.println("Lexicon is " + lp.lex.getClass().getName());
if (op.testOptions.verbose) {
System.err.println("Tags are: " + lp.tagIndex);
// System.err.println("States are: " + lp.pd.stateIndex); // This is too verbose. It was already
// printed out by the below printOptions command if the flag -printStates is given (at training time)!
}
printOptions(false, op);
}
九、执行解析工作
可以以句子的方式解析，也可用ParseFiles类的方法来解析多个文件。
if (testTreebank != null) {
// test parser on treebank
EvaluateTreebank evaluator = new EvaluateTreebank(lp);
evaluator.testOnTreebank(testTreebank);
} else if (argIndex >= args.length) {
// no more arguments, so we just parse our own test sentence
PrintWriter pwOut = op.tlpParams.pw();
PrintWriter pwErr = op.tlpParams.pw(System.err);
ParserQuery pq = lp.parserQuery();
if (pq.parse(op.tlpParams.defaultTestSentence())) {//解析
lp.getTreePrint().printTree(pq.getBestParse(), pwOut);
} else {
pwErr.println("Error. Can't parse test sentence: " +
op.tlpParams.defaultTestSentence());
}
} else {
// We parse filenames given by the remaining arguments，解析
ParseFiles.parseFiles(args, argIndex, tokenized, tokenizerFactory, elementDelimiter, sentenceDelimiter,
escaper, tagDelimiter, op, lp.getTreePrint(), lp);
}