public static void main(String[] args) throws Exception {
if (args.length != 2) {
System.err.println("usage: java TaggerDemo2 modelFile fileToTag");
return;
}
MaxentTagger tagger = new MaxentTagger(args[0]);
TokenizerFactory<CoreLabel> ptbTokenizerFactory =
PTBTokenizer.factory(new CoreLabelTokenFactory(), "untokenizable=noneKeep");
BufferedReader r =
new BufferedReader(new InputStreamReader(new FileInputStream(args[1]), "utf-8"));
PrintWriter pw = new PrintWriter(new OutputStreamWriter(System.out, "utf-8"));
DocumentPreprocessor documentPreprocessor = new DocumentPreprocessor(r);
documentPreprocessor.setTokenizerFactory(ptbTokenizerFactory);
for (List<HasWord> sentence : documentPreprocessor) {
List<TaggedWord> tSentence = tagger.tagSentence(sentence);
pw.println(Sentence.listToString(tSentence, false));
}
// print the adjectives in one more sentence. This shows how to get at words and tags in a
// tagged sentence.
List<HasWord> sent =
Sentence.toWordList(
"The", "slimy", "slug", "crawled", "over", "the", "long", ",", "green", "grass", ".");
List<TaggedWord> taggedSent = tagger.tagSentence(sent);
for (TaggedWord tw : taggedSent) {
if (tw.tag().startsWith("JJ")) {
pw.println(tw.word());
}
}
pw.close();
}
public MUCMentionExtractor(Dictionaries dict, Properties props, Semantics semantics)
throws Exception {
super(dict, semantics);
String fileName = props.getProperty(Constants.MUC_PROP);
fileContents = IOUtils.slurpFile(fileName);
currentOffset = 0;
tokenizerFactory = PTBTokenizer.factory(new CoreLabelTokenFactory(false), "");
stanfordProcessor = loadStanfordProcessor(props);
}
public static ArrayList<TaggedWord> StanfordParse(String sentence, LexicalizedParser lp) {
TokenizerFactory<CoreLabel> tokenizerFactory =
PTBTokenizer.factory(new CoreLabelTokenFactory(), "");
List<CoreLabel> rawWords2 =
tokenizerFactory.getTokenizer(new StringReader(sentence)).tokenize();
Tree parse = lp.apply(rawWords2);
ArrayList<TaggedWord> taggedWords = parse.taggedYield();
return taggedWords;
}
private static List<TypedDependency> getDependencies(String sentence) {
if (pipeline == null) {
loadModels();
}
TokenizerFactory<CoreLabel> tokenizerFactory =
PTBTokenizer.factory(new CoreLabelTokenFactory(), "");
Tokenizer<CoreLabel> tok = tokenizerFactory.getTokenizer(new StringReader(sentence));
List<CoreLabel> rawWords2 = tok.tokenize();
Tree parse = lp.apply(rawWords2);
// parse.pennPrint();
//
// System.out.println(parse.toString());
TreebankLanguagePack tlp = lp.treebankLanguagePack(); // PennTreebankLanguagePack for English
GrammaticalStructureFactory gsf = tlp.grammaticalStructureFactory();
GrammaticalStructure gs = gsf.newGrammaticalStructure(parse);
List<TypedDependency> tdl = gs.typedDependenciesCCprocessed();
return tdl;
}
public static void main(String[] args) // start of the main method
{
System.out.println("\n\n\nSTART\n\n\n"); // print START
try // device to handle potential errors
{
// open file whose path is passed
// as the first argument of the main method:
FileInputStream fis = new FileInputStream(args[0]);
DataInputStream dis = new DataInputStream(fis);
BufferedReader br = new BufferedReader(new InputStreamReader(dis));
// prepare Parser, Tokenizer and Tree printer:
LexicalizedParser lp = new LexicalizedParser("englishPCFG.ser.gz");
TokenizerFactory tf = PTBTokenizer.factory(false, new WordTokenFactory());
TreePrint tp = new TreePrint("penn,typedDependenciesCollapsed");
String sentence; // initialization
// for each line of the file
// retrieve it as a string called 'sentence':
while ((sentence = br.readLine()) != null) {
// print sentence:
System.out.println("\n\n\n\nORIGINAL:\n\n" + sentence);
// put tokens in a list:
List tokens = tf.getTokenizer(new StringReader(sentence)).tokenize();
lp.parse(tokens); // parse the tokens
Tree t = lp.getBestParse(); // get the best parse tree
System.out.println("\nPROCESSED:\n\n");
tp.printTree(t); // print tree
}
dis.close(); // close input file
} catch (Exception e) // catch error if any
{
System.err.println("ERROR: " + e.getMessage()); // print error message
}
System.out.println("\n\n\nTHE END\n\n\n"); // print THE END
} // end of the main method
class StanfordParser {
private final String PCG_MODEL = "edu/stanford/nlp/models/lexparser/englishPCFG.ser.gz";
private final TokenizerFactory<CoreLabel> tokenizerFactory =
PTBTokenizer.factory(new CoreLabelTokenFactory(), "invertible=true");
private final LexicalizedParser parser = LexicalizedParser.loadModel(PCG_MODEL);
private final String serializedClassifier =
"edu/stanford/nlp/models/ner/english.muc.7class.distsim.crf" + ".ser.gz";
private final AbstractSequenceClassifier<CoreLabel> classifier =
CRFClassifier.getClassifierNoExceptions(serializedClassifier);
public ParsedSentence parseSentence(String sentence, boolean removePunctuation) {
if (removePunctuation) {
sentence = cleanSentence(sentence);
}
final Tree posTree = getPosTree(sentence);
return new ParsedSentence(posTree, getDependencies(posTree), findNamedEntities(sentence));
}
public Tense calculateTense(String clause) {
final Tree posTree = getPosTree(clause);
final Tree word = posTree.getLeaves().get(0);
final String pos = word.parent(posTree).label().value().toLowerCase();
if (pos.equals("md")) {
return Tense.FUTURE;
}
if (pos.equals("vbd") || pos.equals("vbn")) {
return Tense.PAST;
}
return Tense.PRESENT;
}
public Map<String, NamedEntity> findNamedEntities(String sentence) {
final Map<String, NamedEntity> namedEntities = new HashMap<>();
final List<Triple<String, Integer, Integer>> nerSubstrings = findNerSubstrings(sentence);
for (final Triple<String, Integer, Integer> substring : nerSubstrings) {
namedEntities.put(
sentence.substring(substring.second(), substring.third()),
NamedEntity.getNamedEntity(substring.first()));
}
return namedEntities;
}
private List<Triple<String, Integer, Integer>> findNerSubstrings(String sentence) {
return classifier.classifyToCharacterOffsets(sentence);
}
private String cleanSentence(String sentence) {
return sentence.replaceAll("\\p{Punct}", "").replaceAll("[ ]+", " ");
}
private Tree getPosTree(String sentence) {
final Tokenizer<CoreLabel> tokenizer =
tokenizerFactory.getTokenizer(new StringReader(sentence));
final List<CoreLabel> tokens = tokenizer.tokenize();
return parser.apply(tokens);
}
private Collection<TypedDependency> getDependencies(Tree sentenceParseTree) {
final TreebankLanguagePack tlp = new PennTreebankLanguagePack();
final GrammaticalStructureFactory gsf = tlp.grammaticalStructureFactory();
final GrammaticalStructure gs = gsf.newGrammaticalStructure(sentenceParseTree);
return gs.typedDependenciesCollapsed();
}
}
@SuppressWarnings("serial")
public class TextSimplification {
public static List<String> replacementList =
new ArrayList<String>() {
{
add("he");
add("him");
add("his");
add("she");
add("her");
add("they");
add("them");
add("their");
add("i");
add("her's");
add("you");
add("your");
add("your's");
add("mine");
add("my");
add("us");
add("we");
// add("it");
// add("its");
// add("this");
// add("that");
}
};
public static String resolvedSentences = "";
private static final String PCG_MODEL = "edu/stanford/nlp/models/lexparser/englishPCFG.ser.gz";
private static final TokenizerFactory<CoreLabel> tokenizerFactory =
PTBTokenizer.factory(new CoreLabelTokenFactory(), "invertible=true");
private static final LexicalizedParser parser = LexicalizedParser.loadModel(PCG_MODEL);
public static void main(String[] args) throws IOException {
// :TODO
// * Do not consider roots with more than 2 words
// * Root should not be he, she her, his, him etc...
// * If it is, den take the last known gender noun and make it the root.
String text = new String(Files.readAllBytes(Paths.get(args[0])), StandardCharsets.UTF_8);
text = text.replace("\n", " ");
// Resolve Anaphora
System.out.println("Anaphora Resolution...");
resolveAnaphora(text);
System.out.println(
"Anaphora Resolution Completed!\nIntermediate Output in \"AnaphoraResolved.txt\"");
writeToFile(resolvedSentences, "AnaphoraResolved.txt");
// Create ParseTrees
System.out.println("Parse Tree Generation...");
startParsing((resolvedSentences));
System.out.println("Parse Tree Generation Completed!\nIntermediate Output in \"Tree.txt\"");
}
public static void resolveAnaphora(String text) {
RedwoodConfiguration.empty().capture(System.err).apply();
Annotation document = new Annotation(text);
Properties props = new Properties();
props.put("annotators", "tokenize, ssplit, pos, lemma, ner, parse, dcoref");
props.put("dcoref.female", "female.unigram.txt");
props.put("dcoref.male", "male.unigram.txt");
StanfordCoreNLP pipeline = new StanfordCoreNLP(props);
pipeline.annotate(document);
RedwoodConfiguration.current().clear().apply();
Map<Integer, CorefChain> graph = document.get(CorefChainAnnotation.class);
List<CoreMap> stnfrdSentences = document.get(SentencesAnnotation.class);
ImmutableMultimap.Builder<Integer, Pair<CorefChain, CorefMention>> records =
ImmutableMultimap.builder();
ImmutableMultimap.Builder<Integer, Pair<CorefChain, CorefMention>> recordsOrdered =
ImmutableMultimap.builder();
graph.forEach(
(key, value) -> {
value
.getMentionMap()
.forEach(
(intPair, corefSet) -> {
corefSet.forEach(
mention -> records.put(mention.sentNum, Pair.of(value, mention)));
});
});
recordsOrdered =
records.orderKeysBy(
new Comparator<Integer>() {
@Override
public int compare(Integer o1, Integer o2) {
return o1 - o2;
}
});
recordsOrdered
.build()
.asMap()
.forEach(
(sentNum, mentionList) -> {
CoreMap sentence = stnfrdSentences.get(sentNum - 1);
List<CoreLabel> stnfrdtokens = sentence.get(TokensAnnotation.class);
mentionList.forEach(
pair -> {
CorefChain chain = pair.getLeft();
CorefMention mention = pair.getRight();
String root = chain.getRepresentativeMention().mentionSpan;
if (!mention.mentionSpan.equalsIgnoreCase(root)
&& (!root.contains(mention.mentionSpan)
&& !mention.mentionSpan.contains(root))
&& (!replacementList.contains(root.toLowerCase()))
&& (root.split("\\s").length < 3)
&& (replacementList.contains(mention.mentionSpan.toLowerCase()))) {
if (mention.mentionSpan.equalsIgnoreCase("her")
|| mention.mentionSpan.equalsIgnoreCase("his")) {
root += "'s";
}
stnfrdtokens.get(mention.startIndex - 1).setOriginalText(root);
}
});
String sent = "";
for (CoreLabel token : stnfrdtokens) {
sent += token.originalText() + " ";
}
;
resolvedSentences += sent + "\n";
});
}
public static Tree parse(String str) {
List<CoreLabel> tokens = tokenize(str);
Tree tree = parser.apply(tokens);
return tree;
}
private static List<CoreLabel> tokenize(String str) {
Tokenizer<CoreLabel> tokenizer = tokenizerFactory.getTokenizer(new StringReader(str));
return tokenizer.tokenize();
}
public static void startParsing(String paragraph) throws FileNotFoundException, IOException {
String parseTrees = "";
// Can we just split on new line as paragraph is already sentence splitted.
Reader reader = new StringReader(paragraph);
DocumentPreprocessor dp = new DocumentPreprocessor(reader);
List<String> sentenceList = new ArrayList<String>();
for (List<HasWord> sentence : dp) {
String sentenceString = Sentence.listToString(sentence);
sentenceList.add(sentenceString);
}
for (String sentence : sentenceList) {
// System.out.println(sentence);
parseTrees += createParseTree(sentence);
}
writeToFile(parseTrees, "trees.txt");
}
public static void writeToFile(String content, String filename) throws IOException {
File file = new File(filename);
file.delete();
FileWriter fout = new FileWriter(filename);
fout.write(content);
fout.close();
}
public static String createParseTree(String sentence) {
Tree tree = parse(sentence);
// System.out.println(tree.toString());
return (tree.toString() + "\n");
}
}
public static void main(String args[]) throws IOException {
long startTime = System.currentTimeMillis();
LexicalizedParser lp = new LexicalizedParser("englishPCFG.ser.gz");
TokenizerFactory tf = PTBTokenizer.factory(false, new WordTokenFactory());
TreePrint tp = new TreePrint("penn,typedDependenciesCollapsed");
String sentence = "Where did the first President die ?";
System.out.println("Enter the question or press enter for default : ");
String tempInput;
BufferedReader b1 = new BufferedReader(new InputStreamReader(System.in));
tempInput = b1.readLine();
if (tempInput.length() == 0)
System.out.println("The question is the default one : " + sentence);
else {
sentence = tempInput;
System.out.println("The question entered is : " + sentence);
}
String sentence1 = PreProcess.removeStopWords1(sentence);
System.out.println(sentence1);
StringTokenizer st1 = new StringTokenizer(sentence1, " ");
int n = 0;
while (st1.hasMoreTokens()) {
String temp1 = st1.nextToken();
// System.out.println("temp replace all is
// "+temp1.replaceAll("'s","").replaceAll("[^A-Za-z]",""));
map.put(n, temp1.replaceAll("'s", "").replaceAll("[^A-Za-z]", ""));
n++;
}
// for(int s=0;s<n;s++)
// System.out.println(map.get(s));
List tokens = tf.getTokenizer(new StringReader(sentence)).tokenize();
lp.parse(tokens); // parse the tokens
Tree t = lp.getBestParse(); // get the best parse tree\
tp.printTree(t);
System.out.println("\nPROCESSED:\n\n"); // tp.printTree(t); // print tree
// dependencies only print
TreebankLanguagePack tlp = new PennTreebankLanguagePack();
GrammaticalStructureFactory gsf = tlp.grammaticalStructureFactory();
GrammaticalStructure gs = gsf.newGrammaticalStructure(t);
// dependencies
// Tree b = t.firstChild();
// System.out.println("\nFirst child of the tree is :\n\n"); tp.printTree(b);
String dependency = gs.typedDependenciesCollapsed().toString();
System.out.println("Dependencies :" + dependency);
// BufferedReader reader = new BufferedReader( new InputStreamReader(System.in) );
// String wordForm = reader.readLine();
String wordForm = "yes";
int i = -1;
String s[][] = new String[20][3];
if (wordForm.equals("yes")) {
StringTokenizer st = new StringTokenizer(dependency, " ([)],");
while (st.hasMoreTokens()) {
String as = st.nextToken();
System.out.println(as);
if (!as.contains("-")) {
i++;
s[i][0] = as;
} else {
s[i][1] = as;
s[i][2] = st.nextToken();
}
}
}
length = i + 1;
interchange1(s);
System.out.println("The sorted version is ");
// System.out.println("\n\n***********Li8 from here on***********");
for (i = 0; i < length; i++) {
for (int j = 0; j < 3; j++) {
System.out.print(s[i][j] + " ");
}
System.out.println();
}
// int adjmatrix[][] = new int[length][length];
System.out.println("What answer type is required: ");
BufferedReader reader = new BufferedReader(new InputStreamReader(System.in));
String answtype = reader.readLine();
String[] temp;
temp = sentence.split(" ", 2);
int g = 0;
int h = 0;
String secque = null;
// dijikstra implementation
int adjmatrix[][] = new int[length][length];
int j = 0;
for (i = 0; i < length; i++) for (j = 0; j < length; j++) adjmatrix[i][j] = 100;
formadj(adjmatrix, s);
print(adjmatrix);
// Dijikstraalgo.dijikstra(adjmatrix,length-2);
// Dijikstraalgo.dijikstra(adjmatrix,length-1);
if (Dijikstraalgo.dijikstra(adjmatrix, length - 1)
- Dijikstraalgo.dijikstra(adjmatrix, length - 2)
>= 0) {
System.out.println("Type 1");
if (makesentence(s, length - 1) == null) {
secque = s[length - 1][2] + " " + s[length - 1][1];
System.out.println(answtype + " is " + s[length - 1][2] + " " + s[length - 1][1] + " ?");
} else {
secque = makesentence(s, length - 1);
System.out.println(answtype + " is " + secque + " ?");
}
} else {
System.out.println("Type 2");
System.out.println(
"Before entering the makesentence function(the cause of the null pointer exception) "
+ s[length - 2][0]
+ " "
+ s[length - 2][1]);
if (makesentence(s, length - 2) == null) {
secque = s[length - 2][2] + " " + s[length - 2][1];
System.out.println(answtype + " is " + s[length - 2][2] + " " + s[length - 2][1] + " ?");
} else {
// System.out.println("null");
secque = makesentence(s, length - 2);
System.out.println(answtype + " is " + secque + " ?");
}
}
// System.out.println("Secque is "+secque.replaceAll("[^A-Za-z ]",""));
System.out.println(sentence.replace(secque.replaceAll("[^A-Za-z ]", ""), ""));
long endTime = System.currentTimeMillis();
System.out.println("The time elapsed is : " + (int) (endTime - startTime) / 1000);
System.out.println("The end");
}
