package edu.stanford.nlp.tagger.util;
import edu.stanford.nlp.ling.Sentence;
import edu.stanford.nlp.ling.TaggedWord;
import edu.stanford.nlp.tagger.maxent.TaggerConfig;
import edu.stanford.nlp.tagger.io.TaggedFileRecord;
import edu.stanford.nlp.util.PropertiesUtils;
import edu.stanford.nlp.util.StringUtils;
import java.util.List;
import java.util.Properties;
import java.util.Random;
/**
* Takes a tagger data file of any format readable by the tagger and
* outputs a new file containing tagged sentences which are prefixes
* of the original data. The prefixes are of random length. If the
* -fullSentence parameter is true, the original sentence is output
* after each prefix.
* <br>
* Input is taken from the tagger file described in "input". Output
* goes to stdout.
*
* @author John Bauer
*/
public class MakePrefixFile {
public static void main(String[] args) {
Properties config = StringUtils.argsToProperties(args);
System.err.println(config);
boolean fullSentence = PropertiesUtils.getBool(config, "fullSentence", false);
Random random = new Random();
String tagSeparator = config.getProperty("tagSeparator", TaggerConfig.TAG_SEPARATOR);
TaggedFileRecord record = TaggedFileRecord.createRecord(config, config.getProperty("input"));
for (List<TaggedWord> sentence : record.reader()) {
int len = random.nextInt(sentence.size()) + 1;
System.out.println(Sentence.listToString(sentence.subList(0, len), false, tagSeparator));
if (fullSentence) {
System.out.println(Sentence.listToString(sentence, false, tagSeparator));
}
}
}
}