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package hmm;
import java.io.PrintStream;
import java.util.HashMap;
import data.Corpus;
public class POS {
//public String trainFilename="../posdata/en_train.conll";
//public static String trainFilename="../posdata/small_train.txt";
public static String trainFilename="../posdata/en_test.conll";
// public static String trainFilename="../posdata/trial1.txt";
public static String testFilename="../posdata/en_test.conll";
//public static String testFilename="../posdata/trial1.txt";
public static String predFilename="../posdata/en_test.predict.conll";
public static String modelFilename="../posdata/posModel.out";
public static final int ITER=20;
public static final int N_STATE=30;
public static void main(String[] args) {
//POS p=new POS();
//POS p=new POS(true);
PRPOS();
}
public POS(){
Corpus c= new Corpus(trainFilename);
//size of vocabulary +1 for unknown tokens
HMM hmm =new HMM(N_STATE, c.getVocabSize()+1,c.getAllData());
for(int i=0;i<ITER;i++){
System.out.println("Iter"+i);
hmm.EM();
if((i+1)%10==0){
hmm.writeModel(modelFilename+i);
}
}
hmm.writeModel(modelFilename);
Corpus test=new Corpus(testFilename,c.vocab);
PrintStream ps= io.FileUtil.openOutFile(predFilename);
int [][]data=test.getAllData();
for(int i=0;i<data.length;i++){
int []tag=hmm.viterbi(data[i]);
String sent[]=test.get(i);
for(int j=0;j<data[i].length;j++){
ps.println(sent[j]+"\t"+tag[j]);
}
ps.println();
}
ps.close();
}
//POS induction with L1/Linf constraints
public static void PRPOS(){
Corpus c= new Corpus(trainFilename);
//size of vocabulary +1 for unknown tokens
HMM hmm =new HMM(N_STATE, c.getVocabSize()+1,c.getAllData());
hmm.o=new HMMObjective(hmm);
for(int i=0;i<ITER;i++){
System.out.println("Iter: "+i);
hmm.PREM();
if((i+1)%10==0){
hmm.writeModel(modelFilename+i);
}
}
hmm.writeModel(modelFilename);
Corpus test=new Corpus(testFilename,c.vocab);
PrintStream ps= io.FileUtil.openOutFile(predFilename);
int [][]data=test.getAllData();
for(int i=0;i<data.length;i++){
int []tag=hmm.viterbi(data[i]);
String sent[]=test.get(i);
for(int j=0;j<data[i].length;j++){
ps.println(sent[j]+"\t"+tag[j]);
}
ps.println();
}
ps.close();
}
public POS(boolean supervised){
Corpus c= new Corpus(trainFilename);
//size of vocabulary +1 for unknown tokens
HMM hmm =new HMM(c.tagVocab.size() , c.getVocabSize()+1,c.getAllData());
hmm.train(c.getTagData());
hmm.writeModel(modelFilename);
Corpus test=new Corpus(testFilename,c.vocab);
HashMap<String, Integer>tagVocab=
(HashMap<String, Integer>) io.SerializedObjects.readSerializedObject(Corpus.tagalphaFilename);
String [] tagdict=new String [tagVocab.size()+1];
for(String key:tagVocab.keySet()){
tagdict[tagVocab.get(key)]=key;
}
tagdict[tagdict.length-1]=Corpus.UNK_TOK;
System.out.println(c.vocab.get("<e>"));
PrintStream ps= io.FileUtil.openOutFile(predFilename);
int [][]data=test.getAllData();
for(int i=0;i<data.length;i++){
int []tag=hmm.viterbi(data[i]);
String sent[]=test.get(i);
for(int j=0;j<data[i].length;j++){
ps.println(sent[j]+"\t"+tagdict[tag[j]]);
}
ps.println();
}
ps.close();
}
}
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