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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.parser.lexparser; 
import edu.stanford.nlp.util.logging.Redwood;

// Looks like the intended behavior of TestTagProjection is:
// 1) Include the basic category (everything before a '-' or '^' annotation)
// 2) Include any annotation introduced with '-'
// 3) Exclude any annotation introduced with '^'
// 4) Annotations introduced with other characters will be included or excluded
//    as determined by the previous annotation or basic category.
//
// This seems awfully haphazard :(
//
//  Roger


/** @author Dan Klein */
public class TestTagProjection implements TagProjection  {

  /** A logger for this class */
  private static Redwood.RedwoodChannels log = Redwood.channels(TestTagProjection.class);

  private static final long serialVersionUID = 9161675508802284114L;

  public String project(String tagStr) {
    StringBuilder sb = new StringBuilder();
    boolean good = true;
    for (int pos = 0, len = tagStr.length(); pos < len; pos++) {
      char c = tagStr.charAt(pos);
      if (c == '-') {
        good = true;
      } else if (c == '^') {
        good = false;
      }
      if (good) {
        sb.append(c);
      }
    }
    String ret = sb.toString();
    // log.info("TTP mapped " + tagStr + " to " + ret);
    return ret;
  }

}