package ivory.core.tokenize;
import ivory.core.Constants;
import java.io.IOException;
import opennlp.tools.tokenize.Tokenizer;
import opennlp.tools.tokenize.TokenizerME;
import opennlp.tools.tokenize.TokenizerModel;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.log4j.Level;
import org.apache.log4j.Logger;
import org.tartarus.snowball.SnowballStemmer;
import edu.umd.hooka.VocabularyWritable;
import edu.umd.hooka.alignment.HadoopAlign;
public class OpenNLPTokenizer extends ivory.core.tokenize.Tokenizer {
private static final Logger sLogger = Logger.getLogger(OpenNLPTokenizer.class);
static{
sLogger.setLevel(Level.INFO);
}
private Tokenizer tokenizer;
private SnowballStemmer stemmer;
private int lang;
private static final int ENGLISH = 0, FRENCH = 1, GERMAN = 2;
private static final String[] classes = {
"org.tartarus.snowball.ext.englishStemmer",
"org.tartarus.snowball.ext.frenchStemmer",
"org.tartarus.snowball.ext.germanStemmer"};
public OpenNLPTokenizer(){
super();
}
@Override
public void configure(Configuration conf){
FileSystem fs;
try {
fs = FileSystem.get(conf);
} catch (IOException e) {
e.printStackTrace();
throw new RuntimeException(e);
}
configure(conf, fs);
}
@Override
public void configure(Configuration conf, FileSystem fs){
setTokenizer(fs, new Path(conf.get(Constants.TokenizerData)));
if (conf.getBoolean(Constants.Stemming, true)) {
setLanguageAndStemmer(conf.get(Constants.Language));
isStemming = true;
}else {
setLanguage(conf.get(Constants.Language));
}
// read stopwords from file (stopwords will be empty set if file does not exist or is empty)
String stopwordsFile = conf.get(Constants.StopwordList);
stopwords = readInput(fs, stopwordsFile);
String stemmedStopwordsFile = conf.get(Constants.StemmedStopwordList);
stemmedStopwords = readInput(fs, stemmedStopwordsFile);
VocabularyWritable vocab;
try {
vocab = (VocabularyWritable) HadoopAlign.loadVocab(new Path(conf.get(Constants.CollectionVocab)), fs);
setVocab(vocab);
} catch (Exception e) {
sLogger.warn("No vocabulary provided to tokenizer.");
vocab = null;
}
isStopwordRemoval = !stopwords.isEmpty();
sLogger.info("Stemmer: " + stemmer + "\nStopword removal is " + isStopwordRemoval +"; number of stopwords: " + stopwords.size() +"; stemmed: " + stemmedStopwords.size());
}
public void setTokenizer(FileSystem fs, Path p){
try {
FSDataInputStream in = fs.open(p);
TokenizerModel model;
model = new TokenizerModel(in);
tokenizer = new TokenizerME(model);
} catch (IOException e) {
e.printStackTrace();
throw new RuntimeException("OpenNLPTokenizer model not available at " + p);
}
}
public void setLanguage(String l){
if(l.startsWith("en")){
lang = ENGLISH;//"english";
}else if(l.startsWith("fr")){
lang = FRENCH;//"french";
}else if(l.equals("german") || l.startsWith("de")){
lang = GERMAN;//"german";
}else{
sLogger.warn("Language not recognized, setting to English!");
}
}
@SuppressWarnings("unchecked")
public void setLanguageAndStemmer(String l){
setLanguage(l);
Class<? extends SnowballStemmer> stemClass;
try {
stemClass = (Class<? extends SnowballStemmer>) Class.forName(classes[lang]);
stemmer = (SnowballStemmer) stemClass.newInstance();
} catch (ClassNotFoundException e) {
sLogger.warn("Stemmer class not recognized!\n" + classes[lang]);
stemmer = null;
return;
} catch (Exception e) {
e.printStackTrace();
throw new RuntimeException(e);
}
}
@Override
public String[] processContent(String text) {
text = preNormalize(text);
if ( lang == FRENCH ) {
text = text.replaceAll("'", "' "); // openNLP does not separate what comes after the apostrophe, which seems to work better
}
String[] tokens = tokenizer.tokenize(text);
StringBuilder tokenized = new StringBuilder();
for ( String token : tokens ){
tokenized.append(token + " ");
}
// do post-normalizations before any stemming or stopword removal
String[] normalizedTokens = postNormalize(tokenized.toString().trim()).split(" ");
tokenized.delete(0, tokenized.length());
for ( int i = 0; i < normalizedTokens.length; i++ ){
String token = normalizedTokens[i].toLowerCase();
if ( isStopwordRemoval() && isDiscard(false, token) ) {
// sLogger.warn("Discarded stopword "+token);
continue;
}
//apply stemming on token
String stemmedToken = stem(token);
//skip if out of vocab
if ( vocab != null && vocab.get(stemmedToken) <= 0) {
// sLogger.warn("Discarded OOV "+token);
continue;
}
tokenized.append( stemmedToken + " " );
}
return tokenized.toString().trim().split(" ");
}
@Override
public int getNumberTokens(String string){
return tokenizer.tokenize(string).length;
}
@Override
public String stem(String token) {
if ( stemmer != null ) {
stemmer.setCurrent(token);
stemmer.stem();
return stemmer.getCurrent();
}else {
return token;
}
}
@Override
public float getOOVRate(String text, VocabularyWritable vocab) {
int countOOV = 0, countAll = 0;
text = preNormalize(text);
String[] tokens = tokenizer.tokenize(text);
StringBuilder tokenized = new StringBuilder();
for ( String token : tokens ){
tokenized.append(token + " ");
}
String[] normalizedTokens = postNormalize(tokenized.toString().trim()).split(" ");
for ( int i = 0; i < normalizedTokens.length; i++ ){
String token = normalizedTokens[i].toLowerCase();
if ( isStopwordRemoval() && isDiscard(false, token) ) {
continue;
}
//apply stemming on token
String stemmedToken = stem(token);
if ( vocab != null && vocab.get(stemmedToken) <= 0) {
countOOV++;
}
countAll++;
}
return (countOOV / (float) countAll);
}
}