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// Stanford Parser -- a probabilistic lexicalized NL CFG parser
// Copyright (c) 2002 - 2014 The Board of Trustees of
// The Leland Stanford Junior University. All Rights Reserved.
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software Foundation,
// Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
//
// For more information, bug reports, fixes, contact:
// Christopher Manning
// Dept of Computer Science, Gates 1A
// Stanford CA 94305-9010
// USA
// [email protected]
// http://nlp.stanford.edu/software/lex-parser.shtml
package edu.stanford.nlp.parser.lexparser;
import edu.stanford.nlp.io.IOUtils;
import edu.stanford.nlp.io.RuntimeIOException;
import edu.stanford.nlp.ling.HasWord;
import edu.stanford.nlp.ling.Word;
import edu.stanford.nlp.ling.TaggedWord;
import edu.stanford.nlp.parser.common.ArgUtils;
import edu.stanford.nlp.parser.common.ParserGrammar;
import edu.stanford.nlp.parser.common.ParserQuery;
import edu.stanford.nlp.parser.common.ParserUtils;
import edu.stanford.nlp.parser.metrics.Eval;
import edu.stanford.nlp.parser.metrics.ParserQueryEval;
import edu.stanford.nlp.process.TokenizerFactory;
import edu.stanford.nlp.util.ErasureUtils;
import java.util.function.Function;
import edu.stanford.nlp.util.HashIndex;
import edu.stanford.nlp.util.Index;
import edu.stanford.nlp.tagger.io.TaggedFileRecord;
import edu.stanford.nlp.trees.*;
import edu.stanford.nlp.util.Generics;
import edu.stanford.nlp.util.Pair;
import edu.stanford.nlp.util.ReflectionLoading;
import edu.stanford.nlp.util.StringUtils;
import edu.stanford.nlp.util.Timing;
import edu.stanford.nlp.util.Triple;
import edu.stanford.nlp.util.concurrent.MulticoreWrapper;
import edu.stanford.nlp.util.concurrent.ThreadsafeProcessor;
import java.io.*;
import java.util.*;
import java.util.zip.GZIPInputStream;
import java.util.zip.GZIPOutputStream;
import java.util.zip.ZipEntry;
import java.util.zip.ZipFile;
import java.lang.reflect.InvocationTargetException;
import java.lang.reflect.Method;
/**
* This class provides the top-level API and command-line interface to a set
* of reasonably good treebank-trained parsers. The name reflects the main
* factored parsing model, which provides a lexicalized PCFG parser
* implemented as a product
* model of a plain PCFG parser and a lexicalized dependency parser.
* But you can also run either component parser alone. In particular, it
* is often useful to do unlexicalized PCFG parsing by using just that
* component parser.
*
* See the package documentation for more details and examples of use.
*
* For information on invoking the parser from the command-line, and for
* a more detailed list of options, see the {@link #main} method.
*
* Note that training on a 1 million word treebank requires a fair amount of
* memory to run. Try -mx1500m to increase the memory allocated by the JVM.
*
* @author Dan Klein (original version)
* @author Christopher Manning (better features, ParserParams, serialization)
* @author Roger Levy (internationalization)
* @author Teg Grenager (grammar compaction, tokenization, etc.)
* @author Galen Andrew (considerable refactoring)
* @author John Bauer (made threadsafe)
*/
public class LexicalizedParser extends ParserGrammar implements Serializable {
public Lexicon lex;
public BinaryGrammar bg;
public UnaryGrammar ug;
public DependencyGrammar dg;
public Index stateIndex, wordIndex, tagIndex;
private Options op;
@Override
public Options getOp() { return op; }
public Reranker reranker; // = null;
@Override
public TreebankLangParserParams getTLPParams() { return op.tlpParams; }
@Override
public TreebankLanguagePack treebankLanguagePack() { return getTLPParams().treebankLanguagePack(); }
@Override
public String[] defaultCoreNLPFlags() {
return getTLPParams().defaultCoreNLPFlags();
}
@Override
public boolean requiresTags() {
return false;
}
private static final String SERIALIZED_PARSER_PROPERTY = "edu.stanford.nlp.SerializedLexicalizedParser";
public static final String DEFAULT_PARSER_LOC = ((System.getenv("NLP_PARSER") != null) ?
System.getenv("NLP_PARSER") :
"edu/stanford/nlp/models/lexparser/englishPCFG.ser.gz");
/**
* Construct a new LexicalizedParser object from a previously
* serialized grammar read from a System property
* edu.stanford.nlp.SerializedLexicalizedParser, or a
* default classpath location
* ({@code edu/stanford/nlp/models/lexparser/englishPCFG.ser.gz}).
*/
public static LexicalizedParser loadModel() {
return loadModel(new Options());
}
/**
* Construct a new LexicalizedParser object from a previously
* serialized grammar read from a System property
* edu.stanford.nlp.SerializedLexicalizedParser, or a
* default classpath location
* ({@code edu/stanford/nlp/models/lexparser/englishPCFG.ser.gz}).
*
* @param op Options to the parser. These get overwritten by the
* Options read from the serialized parser; I think the only
* thing determined by them is the encoding of the grammar
* iff it is a text grammar
*/
public static LexicalizedParser loadModel(Options op,
String ... extraFlags) {
String source = System.getProperty(SERIALIZED_PARSER_PROPERTY);
if (source == null) {
source = DEFAULT_PARSER_LOC;
}
return loadModel(source, op, extraFlags);
}
public static LexicalizedParser loadModel(String parserFileOrUrl,
String ... extraFlags) {
return loadModel(parserFileOrUrl, new Options(), extraFlags);
}
public static LexicalizedParser loadModel(String parserFileOrUrl,
List extraFlags) {
String[] flags = new String[extraFlags.size()];
extraFlags.toArray(flags);
return loadModel(parserFileOrUrl, flags);
}
/**
* Construct a new LexicalizedParser. This loads a grammar
* that was previously assembled and stored as a serialized file.
* @param parserFileOrUrl Filename/URL to load parser from
* @param op Options for this parser. These will normally be overwritten
* by options stored in the file
* @throws IllegalArgumentException If parser data cannot be loaded
*/
public static LexicalizedParser loadModel(String parserFileOrUrl, Options op,
String ... extraFlags) {
// System.err.print("Loading parser from file " + parserFileOrUrl);
LexicalizedParser parser = getParserFromFile(parserFileOrUrl, op);
if (extraFlags.length > 0) {
parser.setOptionFlags(extraFlags);
}
return parser;
}
/**
* Reads one object from the given ObjectInputStream, which is
* assumed to be a LexicalizedParser. Throws a ClassCastException
* if this is not true. The stream is not closed.
*/
public static LexicalizedParser loadModel(ObjectInputStream ois) {
try {
Object o = ois.readObject();
if (o instanceof LexicalizedParser) {
return (LexicalizedParser) o;
}
throw new ClassCastException("Wanted LexicalizedParser, got " +
o.getClass());
} catch (IOException e) {
throw new RuntimeIOException(e);
} catch (ClassNotFoundException e) {
throw new RuntimeException(e);
}
}
public static LexicalizedParser loadModelFromZip(String zipFilename,
String modelName) {
LexicalizedParser parser = null;
try {
File file = new File(zipFilename);
if (file.exists()) {
ZipFile zin = new ZipFile(file);
ZipEntry zentry = zin.getEntry(modelName);
if (zentry != null) {
InputStream in = zin.getInputStream(zentry);
// gunzip it if necessary
if (modelName.endsWith(".gz")) {
in = new GZIPInputStream(in);
}
ObjectInputStream ois = new ObjectInputStream(in);
parser = loadModel(ois);
ois.close();
in.close();
}
zin.close();
} else {
throw new FileNotFoundException("Could not find " + modelName +
" inside " + zipFilename);
}
} catch (IOException e) {
throw new RuntimeIOException(e);
}
return parser;
}
public static LexicalizedParser copyLexicalizedParser(LexicalizedParser parser) {
return new LexicalizedParser(parser.lex, parser.bg, parser.ug, parser.dg, parser.stateIndex, parser.wordIndex, parser.tagIndex, parser.op);
}
public LexicalizedParser(Lexicon lex, BinaryGrammar bg, UnaryGrammar ug, DependencyGrammar dg, Index stateIndex, Index wordIndex, Index tagIndex, Options op) {
this.lex = lex;
this.bg = bg;
this.ug = ug;
this.dg = dg;
this.stateIndex = stateIndex;
this.wordIndex = wordIndex;
this.tagIndex = tagIndex;
this.op = op;
}
/**
* Construct a new LexicalizedParser.
*
* @param trainTreebank a treebank to train from
*/
public static LexicalizedParser trainFromTreebank(Treebank trainTreebank,
GrammarCompactor compactor,
Options op) {
return getParserFromTreebank(trainTreebank, null, 1.0, compactor, op, null, null);
}
public static LexicalizedParser trainFromTreebank(String treebankPath,
FileFilter filt,
Options op) {
return trainFromTreebank(makeTreebank(treebankPath, op, filt), op);
}
public static LexicalizedParser trainFromTreebank(Treebank trainTreebank,
Options op) {
return trainFromTreebank(trainTreebank, null, op);
}
/**
* Will process a list of strings into a list of HasWord and return
* the parse tree associated with that list.
*/
public Tree parseStrings(List lst) {
List words = new ArrayList();
for (String word : lst) {
words.add(new Word(word));
}
return parse(words);
}
/**
* Parses the list of HasWord. If the parse fails for some reason,
* an X tree is returned instead of barfing.
*/
public Tree parse(List lst) {
try {
ParserQuery pq = parserQuery();
if (pq.parse(lst)) {
Tree bestparse = pq.getBestParse();
// -10000 denotes unknown words
bestparse.setScore(pq.getPCFGScore() % -10000.0);
return bestparse;
}
} catch (Exception e) {
System.err.println("Following exception caught during parsing:");
e.printStackTrace();
System.err.println("Recovering using fall through strategy: will construct an (X ...) tree.");
}
// if can't parse or exception, fall through
return ParserUtils.xTree(lst);
}
public List parseMultiple(final List> sentences) {
List trees = new ArrayList();
for (List sentence : sentences) {
trees.add(parse(sentence));
}
return trees;
}
/**
* Will launch multiple threads which calls parse on
* each of the sentences in order, returning the
* resulting parse trees in the same order.
*/
public List parseMultiple(final List> sentences, final int nthreads) {
MulticoreWrapper, Tree> wrapper = new MulticoreWrapper, Tree>(nthreads, new ThreadsafeProcessor, Tree>() {
public Tree process(List sentence) {
return parse(sentence);
}
public ThreadsafeProcessor, Tree> newInstance() {
return this;
}
});
List trees = new ArrayList();
for (List sentence : sentences) {
wrapper.put(sentence);
while (wrapper.peek()) {
trees.add(wrapper.poll());
}
}
wrapper.join();
while (wrapper.peek()) {
trees.add(wrapper.poll());
}
return trees;
}
/** Return a TreePrint for formatting parsed output trees.
* @return A TreePrint for formatting parsed output trees.
*/
public TreePrint getTreePrint() {
return op.testOptions.treePrint(op.tlpParams);
}
/**
* Similar to parse(), but instead of returning an X tree on failure, returns null.
*/
public Tree parseTree(List sentence) {
ParserQuery pq = parserQuery();
if (pq.parse(sentence)) {
return pq.getBestParse();
} else {
return null;
}
}
public List getExtraEvals() {
if (reranker != null) {
return reranker.getEvals();
} else {
return Collections.emptyList();
}
}
public List getParserQueryEvals() {
return Collections.emptyList();
}
@Override
public ParserQuery parserQuery() {
if (reranker == null) {
return new LexicalizedParserQuery(this);
} else {
return new RerankingParserQuery(op, new LexicalizedParserQuery(this), reranker);
}
}
public LexicalizedParserQuery lexicalizedParserQuery() {
return new LexicalizedParserQuery(this);
}
public static LexicalizedParser getParserFromFile(String parserFileOrUrl, Options op) {
LexicalizedParser pd = getParserFromSerializedFile(parserFileOrUrl);
if (pd == null) {
pd = getParserFromTextFile(parserFileOrUrl, op);
}
return pd;
}
private static Treebank makeTreebank(String treebankPath, Options op, FileFilter filt) {
System.err.println("Training a parser from treebank dir: " + treebankPath);
Treebank trainTreebank = op.tlpParams.diskTreebank();
System.err.print("Reading trees...");
if (filt == null) {
trainTreebank.loadPath(treebankPath);
} else {
trainTreebank.loadPath(treebankPath, filt);
}
Timing.tick("done [read " + trainTreebank.size() + " trees].");
return trainTreebank;
}
private static DiskTreebank makeSecondaryTreebank(String treebankPath, Options op, FileFilter filt) {
System.err.println("Additionally training using secondary disk treebank: " + treebankPath + ' ' + filt);
DiskTreebank trainTreebank = op.tlpParams.diskTreebank();
System.err.print("Reading trees...");
if (filt == null) {
trainTreebank.loadPath(treebankPath);
} else {
trainTreebank.loadPath(treebankPath, filt);
}
Timing.tick("done [read " + trainTreebank.size() + " trees].");
return trainTreebank;
}
public Lexicon getLexicon() {
return lex;
}
/**
* Saves the parser defined by pd to the given filename.
* If there is an error, a RuntimeIOException is thrown.
*/
public void saveParserToSerialized(String filename) {
try {
System.err.print("Writing parser in serialized format to file " + filename + ' ');
ObjectOutputStream out = IOUtils.writeStreamFromString(filename);
out.writeObject(this);
out.close();
System.err.println("done.");
} catch (IOException ioe) {
throw new RuntimeIOException(ioe);
}
}
/**
* Saves the parser defined by pd to the given filename.
* If there is an error, a RuntimeIOException is thrown.
*/
public void saveParserToTextFile(String filename) {
if (reranker != null) {
throw new UnsupportedOperationException("Sorry, but parsers with rerankers cannot be saved to text file");
}
try {
System.err.print("Writing parser in text grammar format to file " + filename);
OutputStream os;
if (filename.endsWith(".gz")) {
// it's faster to do the buffering _outside_ the gzipping as here
os = new BufferedOutputStream(new GZIPOutputStream(new FileOutputStream(filename)));
} else {
os = new BufferedOutputStream(new FileOutputStream(filename));
}
PrintWriter out = new PrintWriter(os);
String prefix = "BEGIN ";
out.println(prefix + "OPTIONS");
op.writeData(out);
out.println();
System.err.print(".");
out.println(prefix + "STATE_INDEX");
stateIndex.saveToWriter(out);
out.println();
System.err.print(".");
out.println(prefix + "WORD_INDEX");
wordIndex.saveToWriter(out);
out.println();
System.err.print(".");
out.println(prefix + "TAG_INDEX");
tagIndex.saveToWriter(out);
out.println();
System.err.print(".");
String uwmClazz = ((lex.getUnknownWordModel() == null) ? "null" :
lex.getUnknownWordModel().getClass().getCanonicalName());
out.println(prefix + "LEXICON " + uwmClazz);
lex.writeData(out);
out.println();
System.err.print(".");
out.println(prefix + "UNARY_GRAMMAR");
ug.writeData(out);
out.println();
System.err.print(".");
out.println(prefix + "BINARY_GRAMMAR");
bg.writeData(out);
out.println();
System.err.print(".");
out.println(prefix + "DEPENDENCY_GRAMMAR");
if (dg != null) {
dg.writeData(out);
}
out.println();
System.err.print(".");
out.flush();
out.close();
System.err.println("done.");
} catch (IOException e) {
System.err.println("Trouble saving parser data to ASCII format.");
throw new RuntimeIOException(e);
}
}
private static void confirmBeginBlock(String file, String line) {
if (line == null) {
throw new RuntimeException(file + ": expecting BEGIN block; got end of file.");
} else if (! line.startsWith("BEGIN")) {
throw new RuntimeException(file + ": expecting BEGIN block; got " + line);
}
}
protected static LexicalizedParser getParserFromTextFile(String textFileOrUrl, Options op) {
try {
Timing tim = new Timing();
System.err.print("Loading parser from text file " + textFileOrUrl + ' ');
BufferedReader in = IOUtils.readerFromString(textFileOrUrl);
Timing.startTime();
String line = in.readLine();
confirmBeginBlock(textFileOrUrl, line);
op.readData(in);
System.err.print(".");
line = in.readLine();
confirmBeginBlock(textFileOrUrl, line);
Index stateIndex = HashIndex.loadFromReader(in);
System.err.print(".");
line = in.readLine();
confirmBeginBlock(textFileOrUrl, line);
Index wordIndex = HashIndex.loadFromReader(in);
System.err.print(".");
line = in.readLine();
confirmBeginBlock(textFileOrUrl, line);
Index tagIndex = HashIndex.loadFromReader(in);
System.err.print(".");
line = in.readLine();
confirmBeginBlock(textFileOrUrl, line);
Lexicon lex = op.tlpParams.lex(op, wordIndex, tagIndex);
String uwmClazz = line.split(" +")[2];
if (!uwmClazz.equals("null")) {
UnknownWordModel model = ReflectionLoading.loadByReflection(uwmClazz, op, lex, wordIndex, tagIndex);
lex.setUnknownWordModel(model);
}
lex.readData(in);
System.err.print(".");
line = in.readLine();
confirmBeginBlock(textFileOrUrl, line);
UnaryGrammar ug = new UnaryGrammar(stateIndex);
ug.readData(in);
System.err.print(".");
line = in.readLine();
confirmBeginBlock(textFileOrUrl, line);
BinaryGrammar bg = new BinaryGrammar(stateIndex);
bg.readData(in);
System.err.print(".");
line = in.readLine();
confirmBeginBlock(textFileOrUrl, line);
DependencyGrammar dg = new MLEDependencyGrammar(op.tlpParams, op.directional, op.distance, op.coarseDistance, op.trainOptions.basicCategoryTagsInDependencyGrammar, op, wordIndex, tagIndex);
dg.readData(in);
System.err.print(".");
in.close();
System.err.println(" done [" + tim.toSecondsString() + " sec].");
return new LexicalizedParser(lex, bg, ug, dg, stateIndex, wordIndex, tagIndex, op);
} catch (IOException e) {
e.printStackTrace();
}
return null;
}
public static LexicalizedParser getParserFromSerializedFile(String serializedFileOrUrl) {
try {
Timing tim = new Timing();
System.err.print("Loading parser from serialized file " + serializedFileOrUrl + " ...");
ObjectInputStream in = IOUtils.readStreamFromString(serializedFileOrUrl);
LexicalizedParser pd = loadModel(in);
in.close();
System.err.println(" done [" + tim.toSecondsString() + " sec].");
return pd;
} catch (InvalidClassException ice) {
// For this, it's not a good idea to continue and try it as a text file!
System.err.println(); // as in middle of line from above message
throw new RuntimeException("Invalid class in file: " + serializedFileOrUrl, ice);
} catch (FileNotFoundException fnfe) {
// For this, it's not a good idea to continue and try it as a text file!
System.err.println(); // as in middle of line from above message
throw new RuntimeException("File not found: " + serializedFileOrUrl, fnfe);
} catch (StreamCorruptedException sce) {
// suppress error message, on the assumption that we've really got
// a text grammar, and that'll be tried next
System.err.println();
} catch (Exception e) {
System.err.println(); // as in middle of line from above message
e.printStackTrace();
}
return null;
}
private static void printOptions(boolean train, Options op) {
op.display();
if (train) {
op.trainOptions.display();
} else {
op.testOptions.display();
}
op.tlpParams.display();
}
public static TreeAnnotatorAndBinarizer buildTrainBinarizer(Options op) {
TreebankLangParserParams tlpParams = op.tlpParams;
if (!op.trainOptions.leftToRight) {
return new TreeAnnotatorAndBinarizer(tlpParams, op.forceCNF, !op.trainOptions.outsideFactor(), !op.trainOptions.predictSplits, op);
} else {
return new TreeAnnotatorAndBinarizer(tlpParams.headFinder(), new LeftHeadFinder(), tlpParams, op.forceCNF, !op.trainOptions.outsideFactor(), !op.trainOptions.predictSplits, op);
}
}
public static CompositeTreeTransformer buildTrainTransformer(Options op) {
TreeAnnotatorAndBinarizer binarizer = buildTrainBinarizer(op);
return buildTrainTransformer(op, binarizer);
}
public static CompositeTreeTransformer buildTrainTransformer(Options op, TreeAnnotatorAndBinarizer binarizer) {
TreebankLangParserParams tlpParams = op.tlpParams;
TreebankLanguagePack tlp = tlpParams.treebankLanguagePack();
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);
}
trainTransformer.addTransformer(binarizer);
if (op.wordFunction != null) {
TreeTransformer wordFunctionTransformer =
new TreeLeafLabelTransformer(op.wordFunction);
trainTransformer.addTransformer(wordFunctionTransformer);
}
return trainTransformer;
}
/** @return a pair of binaryTrainTreebank,binaryTuneTreebank.
*/
public static Triple getAnnotatedBinaryTreebankFromTreebank(Treebank trainTreebank,
Treebank secondaryTreebank,
Treebank tuneTreebank,
Options op) {
// setup tree transforms
TreebankLangParserParams tlpParams = op.tlpParams;
TreebankLanguagePack tlp = tlpParams.treebankLanguagePack();
if (op.testOptions.verbose) {
PrintWriter pwErr = tlpParams.pw(System.err);
pwErr.print("Training ");
pwErr.println(trainTreebank.textualSummary(tlp));
if (secondaryTreebank != null) {
pwErr.print("Secondary training ");
pwErr.println(secondaryTreebank.textualSummary(tlp));
}
}
System.err.print("Binarizing trees...");
TreeAnnotatorAndBinarizer binarizer = buildTrainBinarizer(op);
CompositeTreeTransformer trainTransformer = buildTrainTransformer(op, binarizer);
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) {
List list = new ArrayList(op.trainOptions.splitters);
Collections.sort(list);
System.err.println("Parent split categories: " + list);
}
}
if (op.trainOptions.selectivePostSplit) {
// Do all the transformations once just to learn selective splits on annotated categories
TreeTransformer 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) {
System.err.println("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);
for (Tree tree : 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);
}
Timing.tick("done.");
if (op.testOptions.verbose) {
binarizer.dumpStats();
}
return new Triple(trainTreebank, secondaryTreebank, tuneTreebank);
}
private static void removeDeleteSplittersFromSplitters(TreebankLanguagePack tlp, Options op) {
if (op.trainOptions.deleteSplitters != null) {
List deleted = new ArrayList();
for (String del : op.trainOptions.deleteSplitters) {
String baseDel = tlp.basicCategory(del);
boolean checkBasic = del.equals(baseDel);
for (Iterator 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);
}
}
}
if (op.testOptions.verbose) {
System.err.println("Removed from vertical splitters: " + deleted);
}
}
}
// TODO: Make below method work with arbitrarily large secondary treebank via iteration
// TODO: Have weight implemented for training lexicon
/**
* A method for training from two different treebanks, the second of which is presumed
* to be orders of magnitude larger.
*
* Trees are not read into memory but processed as they are read from disk.
*
* A weight (typically <= 1) can be put on the second treebank.
*
* @param trainTreebank A treebank to train from
* @param secondaryTrainTreebank Another treebank to train from
* @param weight A weight factor to give the secondary treebank. If the weight
* is 0.25, each example in the secondaryTrainTreebank will be treated as
* 1/4 of an example sentence.
* @param compactor A class for compacting grammars. May be null.
* @param op Options for how the grammar is built from the treebank
* @param tuneTreebank A treebank to tune free params on (may be null)
* @param extraTaggedWords A list of words to add to the Lexicon
* @return The trained LexicalizedParser
*/
public static LexicalizedParser
getParserFromTreebank(Treebank trainTreebank,
Treebank secondaryTrainTreebank,
double weight,
GrammarCompactor compactor,
Options op,
Treebank tuneTreebank,
List> extraTaggedWords)
{
// System.err.println("Currently " + new Date()); // now printed when command-line args are printed
printOptions(true, op);
Timing.startTime();
Triple treebanks = TreeAnnotatorAndBinarizer.getAnnotatedBinaryTreebankFromTreebank(trainTreebank, secondaryTrainTreebank, tuneTreebank, op);
Timing.tick("done.");
Treebank trainTreebankRaw = trainTreebank;
trainTreebank = treebanks.first();
secondaryTrainTreebank = treebanks.second();
tuneTreebank = treebanks.third();
// +1 to account for the boundary symbol
trainTreebank = new FilteringTreebank(trainTreebank, new LengthTreeFilter(op.trainOptions.trainLengthLimit + 1));
if (secondaryTrainTreebank != null) {
secondaryTrainTreebank = new FilteringTreebank(secondaryTrainTreebank, new LengthTreeFilter(op.trainOptions.trainLengthLimit + 1));
}
if (tuneTreebank != null) {
tuneTreebank = new FilteringTreebank(tuneTreebank, new LengthTreeFilter(op.trainOptions.trainLengthLimit + 1));
}
Index stateIndex;
Index wordIndex;
Index tagIndex;
Pair bgug;
Lexicon lex;
if (op.trainOptions.predictSplits) {
SplittingGrammarExtractor extractor = new SplittingGrammarExtractor(op);
System.err.print("Extracting PCFG...");
// TODO: make use of the tagged text
if (secondaryTrainTreebank == null) {
extractor.extract(trainTreebank);
} else {
extractor.extract(trainTreebank, 1.0, secondaryTrainTreebank, weight);
}
bgug = extractor.bgug;
lex = extractor.lex;
stateIndex = extractor.stateIndex;
wordIndex = extractor.wordIndex;
tagIndex = extractor.tagIndex;
Timing.tick("done.");
} else {
stateIndex = new HashIndex();
wordIndex = new HashIndex();
tagIndex = new HashIndex();
// extract grammars
BinaryGrammarExtractor bgExtractor = new BinaryGrammarExtractor(op, stateIndex);
// Extractor lexExtractor = new LexiconExtractor();
//TreeExtractor uwmExtractor = new UnknownWordModelExtractor(trainTreebank.size());
System.err.print("Extracting PCFG...");
if (secondaryTrainTreebank == null) {
bgug = bgExtractor.extract(trainTreebank);
} else {
bgug = bgExtractor.extract(trainTreebank, 1.0,
secondaryTrainTreebank, weight);
}
Timing.tick("done.");
System.err.print("Extracting Lexicon...");
lex = op.tlpParams.lex(op, wordIndex, tagIndex);
double trainSize = trainTreebank.size();
if (secondaryTrainTreebank != null) {
trainSize += (secondaryTrainTreebank.size() * weight);
}
if (extraTaggedWords != null) {
trainSize += extraTaggedWords.size();
}
lex.initializeTraining(trainSize);
// wsg2012: The raw treebank has CoreLabels, which we need for FactoredLexicon
// training. If TreeAnnotator is updated so that it produces CoreLabels, then we can
// remove the trainTreebankRaw.
lex.train(trainTreebank, trainTreebankRaw);
if (secondaryTrainTreebank != null) {
lex.train(secondaryTrainTreebank, weight);
}
if (extraTaggedWords != null) {
for (List sentence : extraTaggedWords) {
// TODO: specify a weight?
lex.trainUnannotated(sentence, 1.0);
}
}
lex.finishTraining();
Timing.tick("done.");
}
//TODO: wsg2011 Not sure if this should come before or after
//grammar compaction
if (op.trainOptions.ruleSmoothing) {
System.err.print("Smoothing PCFG...");
Function,Pair> smoother = new LinearGrammarSmoother(op.trainOptions, stateIndex, tagIndex);
bgug = smoother.apply(bgug);
Timing.tick("done.");
}
if (compactor != null) {
System.err.print("Compacting grammar...");
Triple, UnaryGrammar, BinaryGrammar> compacted = compactor.compactGrammar(bgug, stateIndex);
stateIndex = compacted.first();
bgug.setFirst(compacted.second());
bgug.setSecond(compacted.third());
Timing.tick("done.");
}
System.err.print("Compiling grammar...");
BinaryGrammar bg = bgug.second;
bg.splitRules();
UnaryGrammar ug = bgug.first;
ug.purgeRules();
Timing.tick("done");
DependencyGrammar dg = null;
if (op.doDep) {
System.err.print("Extracting Dependencies...");
AbstractTreeExtractor dgExtractor = new MLEDependencyGrammarExtractor(op, wordIndex, tagIndex);
if (secondaryTrainTreebank == null) {
dg = dgExtractor.extract(trainTreebank);
} else {
dg = dgExtractor.extract(trainTreebank, 1.0, secondaryTrainTreebank, weight);
}
//System.err.print("Extracting Unknown Word Model...");
//UnknownWordModel uwm = (UnknownWordModel)uwmExtractor.extract(trainTreebank);
//Timing.tick("done.");
Timing.tick("done.");
if (tuneTreebank != null) {
System.err.print("Tuning Dependency Model...");
dg.setLexicon(lex); // MG2008: needed if using PwGt model
dg.tune(tuneTreebank);
Timing.tick("done.");
}
}
System.err.println("Done training parser.");
if (op.trainOptions.trainTreeFile!=null) {
try {
System.err.print("Writing out binary trees to "+ op.trainOptions.trainTreeFile+"...");
IOUtils.writeObjectToFile(trainTreebank, op.trainOptions.trainTreeFile);
IOUtils.writeObjectToFile(secondaryTrainTreebank, op.trainOptions.trainTreeFile);
Timing.tick("done.");
} catch (Exception e) {
System.err.println("Problem writing out binary trees.");
}
}
return new LexicalizedParser(lex, bg, ug, dg, stateIndex, wordIndex, tagIndex, op);
}
/**
* This will set options to the parser, in a way exactly equivalent to
* passing in the same sequence of command-line arguments. This is a useful
* convenience method when building a parser programmatically. The options
* passed in should
* be specified like command-line arguments, including with an initial
* minus sign.
*
* Notes: This can be used to set parsing-time flags for a
* serialized parser. You can also still change things serialized
* in Options, but this will probably degrade parsing performance.
* The vast majority of command line flags can be passed to this
* method, but you cannot pass in options that specify the treebank
* or grammar to be loaded, the grammar to be written, trees or
* files to be parsed or details of their encoding, nor the
* TreebankLangParserParams (-tLPP) to use. The
* TreebankLangParserParams should be set up on construction of a
* LexicalizedParser, by constructing an Options that uses
* the required TreebankLangParserParams, and passing that to a
* LexicalizedParser constructor. Note that despite this
* method being an instance method, many flags are actually set as
* static class variables.
*
* @param flags Arguments to the parser, for example,
* {"-outputFormat", "typedDependencies", "-maxLength", "70"}
* @throws IllegalArgumentException If an unknown flag is passed in
*/
public void setOptionFlags(String... flags) {
op.setOptions(flags);
}
/**
* A main program for using the parser with various options.
* This program can be used for building and serializing
* a parser from treebank data, for parsing sentences from a file
* or URL using a serialized or text grammar parser,
* and (mainly for parser quality testing)
* for training and testing a parser on a treebank all in one go.
*
*
* Sample Usages:
*
* - Train a parser (saved to serializedGrammarFilename)
* from a directory of trees (trainFilesPath, with an optional fileRange, e.g., 0-1000):
*
java -mx1500m edu.stanford.nlp.parser.lexparser.LexicalizedParser [-v] -train trainFilesPath [fileRange] -saveToSerializedFile serializedGrammarFilename
*
*
* - Train a parser (not saved) from a directory of trees, and test it (reporting scores) on a directory of trees
*
java -mx1500m edu.stanford.nlp.parser.lexparser.LexicalizedParser [-v] -train trainFilesPath [fileRange] -testTreebank testFilePath [fileRange]
*
*
* - Parse one or more files, given a serialized grammar and a list of files
*
java -mx512m edu.stanford.nlp.parser.lexparser.LexicalizedParser [-v] serializedGrammarPath filename [filename] ...
*
*
* - Test and report scores for a serialized grammar on trees in an output directory
*
java -mx512m edu.stanford.nlp.parser.lexparser.LexicalizedParser [-v] -loadFromSerializedFile serializedGrammarPath -testTreebank testFilePath [fileRange]
*
*
*
*
* If the serializedGrammarPath ends in .gz,
* then the grammar is written and read as a compressed file (GZip).
* If the serializedGrammarPath is a URL, starting with
* http://, then the parser is read from the URL.
* A fileRange specifies a numeric value that must be included within a
* filename for it to be used in training or testing (this works well with
* most current treebanks). It can be specified like a range of pages to be
* printed, for instance as 200-2199 or
* 1-300,500-725,9000 or just as 1 (if all your
* trees are in a single file, just give a dummy argument such as
* 0 or 1).
* The parser can write a grammar as either a serialized Java object file
* or in a text format (or as both), specified with the following options:
*
*
* java edu.stanford.nlp.parser.lexparser.LexicalizedParser
* [-v] -train
* trainFilesPath [fileRange] [-saveToSerializedFile grammarPath]
* [-saveToTextFile grammarPath]
* If no files are supplied to parse, then a hardwired sentence
* is parsed.
*
* In the same position as the verbose flag (-v), many other
* options can be specified. The most useful to an end user are:
*
* -tLPP class Specify a different
* TreebankLangParserParams, for when using a different language or
* treebank (the default is English Penn Treebank). This option MUST occur
* before any other language-specific options that are used (or else they
* are ignored!).
* (It's usually a good idea to specify this option even when loading a
* serialized grammar; it is necessary if the language pack specifies a
* needed character encoding or you wish to specify language-specific
* options on the command line.)-encoding charset Specify the character encoding of the
* input and output files. This will override the value in the
* TreebankLangParserParams, provided this option appears
* after any -tLPP option.-tokenized Says that the input is already separated
* into whitespace-delimited tokens. If this option is specified, any
* tokenizer specified for the language is ignored, and a universal (Unicode)
* tokenizer, which divides only on whitespace, is used.
* Unless you also specify
* -escaper, the tokens must all be correctly
* tokenized tokens of the appropriate treebank for the parser to work
* well (for instance, if using the Penn English Treebank, you must have
* coded "(" as "-LRB-", "3/4" as "3\/4", etc.)-escaper class Specify a class of type
* {@link Function}<List<HasWord>,List<HasWord>> to do
* customized escaping of tokenized text. This class will be run over the
* tokenized text and can fix the representation of tokens. For instance,
* it could change "(" to "-LRB-" for the Penn English Treebank. A
* provided escaper that does such things for the Penn English Treebank is
* edu.stanford.nlp.process.PTBEscapingProcessor
* -tokenizerFactory class Specifies a
* TokenizerFactory class to be used for tokenization-tokenizerOptions options Specifies options to a
* TokenizerFactory class to be used for tokenization. A comma-separated
* list. For PTBTokenizer, options of interest include
* americanize=false and asciiQuotes (for German).
* Note that any choice of tokenizer options that conflicts with the
* tokenization used in the parser training data will likely degrade parser
* performance. -sentences token Specifies a token that marks sentence
* boundaries. A value of newline causes sentence breaking on
* newlines. A value of onePerElement causes each element
* (using the XML -parseInside option) to be treated as a
* sentence. All other tokens will be interpreted literally, and must be
* exactly the same as tokens returned by the tokenizer. For example,
* you might specify "|||" and put that symbol sequence as a token between
* sentences.
* If no explicit sentence breaking option is chosen, sentence breaking
* is done based on a set of language-particular sentence-ending patterns.
* -parseInside element Specifies that parsing should only
* be done for tokens inside the indicated XML-style
* elements (done as simple pattern matching, rather than XML parsing).
* For example, if this is specified as sentence, then
* the text inside the sentence element
* would be parsed.
* Using "-parseInside s" gives you support for the input format of
* Charniak's parser. Sentences cannot span elements. Whether the
* contents of the element are treated as one sentence or potentially
* multiple sentences is controlled by the -sentences flag.
* The default is potentially multiple sentences.
* This option gives support for extracting and parsing
* text from very simple SGML and XML documents, and is provided as a
* user convenience for that purpose. If you want to really parse XML
* documents before NLP parsing them, you should use an XML parser, and then
* call to a LexicalizedParser on appropriate CDATA.
* -tagSeparator char Specifies to look for tags on words
* following the word and separated from it by a special character
* char. For instance, many tagged corpora have the
* representation "house/NN" and you would use -tagSeparator /.
* Notes: This option requires that the input be pretokenized.
* The separator has to be only a single character, and there is no
* escaping mechanism. However, splitting is done on the last
* instance of the character in the token, so that cases like
* "3\/4/CD" are handled correctly. The parser will in all normal
* circumstances use the tag you provide, but will override it in the
* case of very common words in cases where the tag that you provide
* is not one that it regards as a possible tagging for the word.
* The parser supports a format where only some of the words in a sentence
* have a tag (if you are calling the parser programmatically, you indicate
* them by having them implement the HasTag interface).
* You can do this at the command-line by only having tags after some words,
* but you are limited by the fact that there is no way to escape the
* tagSeparator character.-maxLength leng Specify the longest sentence that
* will be parsed (and hence indirectly the amount of memory
* needed for the parser). If this is not specified, the parser will
* try to dynamically grow its parse chart when long sentence are
* encountered, but may run out of memory trying to do so.-outputFormat styles Choose the style(s) of output
* sentences: penn for prettyprinting as in the Penn
* treebank files, or oneline for printing sentences one
* per line, words, wordsAndTags,
* dependencies, typedDependencies,
* or typedDependenciesCollapsed.
* Multiple options may be specified as a comma-separated
* list. See TreePrint class for further documentation.-outputFormatOptions Provide options that control the
* behavior of various -outputFormat choices, such as
* lexicalize, stem, markHeadNodes,
* or xml. {@link edu.stanford.nlp.trees.TreePrint}
* Options are specified as a comma-separated list.-writeOutputFiles Write output files corresponding
* to the input files, with the same name but a ".stp"
* file extension. The format of these files depends on the
* outputFormat option. (If not specified, output is sent
* to stdout.)-outputFilesExtension The extension that is appended to
* the filename that is being parsed to produce an output file name (with the
* -writeOutputFiles option). The default is stp. Don't
* include the period.
* -outputFilesDirectory The directory in which output
* files are written (when the -writeOutputFiles option is specified).
* If not specified, output files are written in the same directory as the
* input files.
* -nthreads Parsing files and testing on treebanks
* can use multiple threads. This option tells the parser how many
* threads to use. A negative number indicates to use as many
* threads as the machine has cores.
*
* See also the package documentation for more details and examples of use.
*
* @param args Command line arguments, as above
*/
public static void main(String[] args) {
boolean train = false;
boolean saveToSerializedFile = false;
boolean saveToTextFile = false;
String serializedInputFileOrUrl = null;
String textInputFileOrUrl = null;
String serializedOutputFileOrUrl = null;
String textOutputFileOrUrl = null;
String treebankPath = null;
Treebank testTreebank = null;
Treebank tuneTreebank = null;
String testPath = null;
FileFilter testFilter = null;
String tunePath = null;
FileFilter tuneFilter = null;
FileFilter trainFilter = null;
String secondaryTreebankPath = null;
double secondaryTreebankWeight = 1.0;
FileFilter secondaryTrainFilter = null;
// variables needed to process the files to be parsed
TokenizerFactory tokenizerFactory = null;
String tokenizerOptions = null;
String tokenizerFactoryClass = null;
String tokenizerMethod = null;
boolean tokenized = false; // whether or not the input file has already been tokenized
Function, List> escaper = null;
String tagDelimiter = null;
String sentenceDelimiter = null;
String elementDelimiter = null;
int argIndex = 0;
if (args.length < 1) {
System.err.println("Basic usage (see Javadoc for more): java edu.stanford.nlp.parser.lexparser.LexicalizedParser parserFileOrUrl filename*");
return;
}
Options op = new Options();
List optionArgs = new ArrayList();
String encoding = null;
// while loop through option arguments
while (argIndex < args.length && args[argIndex].charAt(0) == '-') {
if (args[argIndex].equalsIgnoreCase("-train") ||
args[argIndex].equalsIgnoreCase("-trainTreebank")) {
train = true;
Pair treebankDescription = ArgUtils.getTreebankDescription(args, argIndex, "-train");
argIndex = argIndex + ArgUtils.numSubArgs(args, argIndex) + 1;
treebankPath = treebankDescription.first();
trainFilter = treebankDescription.second();
} else if (args[argIndex].equalsIgnoreCase("-train2")) {
// train = true; // cdm july 2005: should require -train for this
Triple treebankDescription = ArgUtils.getWeightedTreebankDescription(args, argIndex, "-train2");
argIndex = argIndex + ArgUtils.numSubArgs(args, argIndex) + 1;
secondaryTreebankPath = treebankDescription.first();
secondaryTrainFilter = treebankDescription.second();
secondaryTreebankWeight = treebankDescription.third();
} else if (args[argIndex].equalsIgnoreCase("-tLPP") && (argIndex + 1 < args.length)) {
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")) {
// 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")) {
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")) {
tokenizerOptions = args[argIndex + 1];
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-tokenizerFactory")) {
tokenizerFactoryClass = args[argIndex + 1];
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-tokenizerMethod")) {
tokenizerMethod = args[argIndex + 1];
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-sentences")) {
sentenceDelimiter = args[argIndex + 1];
if (sentenceDelimiter.equalsIgnoreCase("newline")) {
sentenceDelimiter = "\n";
}
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-parseInside")) {
elementDelimiter = args[argIndex + 1];
argIndex += 2;
} else if (args[argIndex].equalsIgnoreCase("-tagSeparator")) {
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")) {
Pair 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 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
// all other arguments are order dependent and
// are processed in order below
if (tuneFilter != null || tunePath != null) {
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);
}
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> extraTaggedWords = null;
if (op.trainOptions.taggedFiles != null) {
extraTaggedWords = new ArrayList>();
List fileRecords = TaggedFileRecord.createRecords(new Properties(), op.trainOptions.taggedFiles);
for (TaggedFileRecord record : fileRecords) {
for (List sentence : record.reader()) {
extraTaggedWords.add(sentence);
}
}
}
lp = getParserFromTreebank(trainTreebank, secondaryTrainTreebank, secondaryTreebankWeight, compactor, op, tuneTreebank, extraTaggedWords);
} else if (textInputFileOrUrl != null) {
// so we load the parser from a text grammar file
lp = getParserFromTextFile(textInputFileOrUrl, op);
} else {
// so we load a serialized parser
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;
}
}
// set up tokenizerFactory with options if provided
if (tokenizerFactoryClass != null || tokenizerOptions != null) {
try {
if (tokenizerFactoryClass != null) {
Class> 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. use the parser
// langpack's factory and set its options
tokenizerFactory = lp.op.langpack().getTokenizerFactory();
tokenizerFactory.setOptions(tokenizerOptions);
}
} catch (IllegalAccessException | InvocationTargetException | ClassNotFoundException | NoSuchMethodException e) {
System.err.println("Couldn't instantiate TokenizerFactory " + tokenizerFactoryClass + " with options " + tokenizerOptions);
throw new RuntimeException(e);
}
}
// 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);
}
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);
}
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");
}
}
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);
}
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())) {
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
ParseFiles.parseFiles(args, argIndex, tokenized, tokenizerFactory, elementDelimiter, sentenceDelimiter, escaper, tagDelimiter, op, lp.getTreePrint(), lp);
}
} // end main
private static final long serialVersionUID = 2;
} // end class LexicalizedParser