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Stanford CoreNLP provides a set of natural language analysis tools which can take raw English language text input and give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, times, and numeric quantities, mark up the structure of sentences in terms of phrases and word dependencies, and indicate which noun phrases refer to the same entities. It provides the foundational building blocks for higher level text understanding applications.

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package edu.stanford.nlp.process;

import java.io.Reader;
import java.io.Serializable;
import java.util.Collections;
import java.util.Iterator;
import java.util.List;
import java.util.Properties;

import edu.stanford.nlp.ling.CoreLabel;
import edu.stanford.nlp.ling.HasWord;
import edu.stanford.nlp.util.PropertiesUtils;
import edu.stanford.nlp.util.StringUtils;

/** A tokenizer that works by calling a WordSegmenter.
 *  This is used for Chinese and Arabic.
 *
 *  @author Galen Andrew
 *  @author Spence Green
 */
public class WordSegmentingTokenizer extends AbstractTokenizer {

  private Iterator wordIter;
  private Tokenizer tok;
  private WordSegmenter wordSegmenter;

  public WordSegmentingTokenizer(WordSegmenter segmenter, Reader r) {
    this(segmenter, WhitespaceTokenizer.newCoreLabelWhitespaceTokenizer(r));
  }

  public WordSegmentingTokenizer(WordSegmenter segmenter, Tokenizer tokenizer) {
    wordSegmenter = segmenter;
    tok = tokenizer;
  }

  @Override
  protected HasWord getNext() {
    while (wordIter == null || ! wordIter.hasNext()) {
      if ( ! tok.hasNext()) {
        return null;
      }
      CoreLabel token = tok.next();
      String s = token.word();
      if (s == null) {
        return null;
      }
      if (s.equals(WhitespaceLexer.NEWLINE)) {
        // if newlines were significant, we should make sure to return
        // them when we see them
        List se = Collections.singletonList(token);
        wordIter = se.iterator();
      } else {
        List se = wordSegmenter.segment(s);
        wordIter = se.iterator();
      }
    }
    return wordIter.next();
  }

  public static TokenizerFactory factory(WordSegmenter wordSegmenter) {
    return new WordSegmentingTokenizerFactory(wordSegmenter);
  }

  private static class WordSegmentingTokenizerFactory implements TokenizerFactory, Serializable {
    private static final long serialVersionUID = -4697961121607489828L;

    boolean tokenizeNLs = false;
    private WordSegmenter segmenter;

    public WordSegmentingTokenizerFactory(WordSegmenter wordSegmenter) {
      segmenter = wordSegmenter;
    }

    public Iterator getIterator(Reader r) {
      return getTokenizer(r);
    }

    public Tokenizer getTokenizer(Reader r) {
      return getTokenizer(r, null);
    }

    public Tokenizer getTokenizer(Reader r, String extraOptions) {
      boolean tokenizeNewlines = this.tokenizeNLs;
      if (extraOptions != null) {
        Properties prop = StringUtils.stringToProperties(extraOptions);
        tokenizeNewlines = PropertiesUtils.getBool(prop, "tokenizeNLs", this.tokenizeNLs);
      }

      return new WordSegmentingTokenizer(segmenter, WhitespaceTokenizer.newCoreLabelWhitespaceTokenizer(r, tokenizeNewlines));
    }

    public void setOptions(String options) {
      Properties prop = StringUtils.stringToProperties(options);
      tokenizeNLs = PropertiesUtils.getBool(prop, "tokenizeNLs", tokenizeNLs);
    }
  }
}