Java Sentence.add方法代码示例

import edu.stanford.nlp.ling.Sentence; //导入方法依赖的package包/类
private static Sentence<TaggedWord> myExtractor(Tree t, Sentence<TaggedWord> ty) {
  Tree[] kids = t.children();
  // this inlines the content of t.isPreTerminal()
  if (kids.length == 1 && kids[0].isLeaf()) {
    if (t.label() instanceof HasTag) {
      //   System.err.println("Object is: " + ((CategoryWordTag) t.label()).toString("full"));
      ty.add(new TaggedWord(kids[0].label().value(), ((HasTag) t.label()).tag()));
    } else {
      //   System.err.println("Object is: " + StringUtils.getShortClassName(t.label()) + " " + t.label());
      ty.add(new TaggedWord(kids[0].label().value(), t.label().value()));
    }
  } else {
    for (int i = 0; i < kids.length; i++) {
      myExtractor(kids[i], ty);
    }
  }
  return ty;
}
 

import edu.stanford.nlp.ling.Sentence; //导入方法依赖的package包/类
/**
 * Gets the yield of the tree.  The <code>Label</code> of all leaf nodes
 * is returned
 * as a list ordered by the natural left to right order of the
 * leaves.  Null values, if any, are inserted into the list like any
 * other value.
 * <p><i>Implementation notes:</i> c. 2003: This has been rewritten to thread, so only one List
 * is used. 2007: This method was duplicated to start to give type safety to Sentence.
 * This method will now make a Word for any Leaf which does not itself implement HasWord, and
 * put the Word into the Sentence, so the Sentence elements MUST implement HasWord.
 *
 * @param y The list in which the yield of the tree will be placed.
 *          Normally, this will be empty when the routine is called, but
 *          if not, the new yield is added to the end of the list.
 * @return a <code>List</code> of the data in the tree's leaves.
 */
@SuppressWarnings("unchecked")
public <X extends HasWord> Sentence<X> yield(Sentence<X> y) {
  if (isLeaf()) {
    Label lab = label();
    // cdm: this is new hacked in stuff in Mar 2007 so we can now have a
    // well-typed version of a Sentence, whose objects MUST implement HasWord
    if (lab instanceof HasWord) {
      y.add((X) lab);
    } else {
      y.add((X) new Word(lab));
    }
  } else {
    Tree[] kids = children();
    for (int i = 0; i < kids.length; i++) {
      kids[i].yield(y);
    }
  }
  return y;
}
 

import edu.stanford.nlp.ling.Sentence; //导入方法依赖的package包/类
/**
 * @param strings
 * @return
 */
private Sentence<? extends HasWord> listToSentence(	List<String> strings) {
	Sentence<HasWord> sentence = new Sentence<HasWord>();
	for (String str : strings)
		sentence.add(new Word(str));
	return sentence;
}
 

import edu.stanford.nlp.ling.Sentence; //导入方法依赖的package包/类
private static Sentence<Word> wordify(List wList) {
  Sentence<Word> s = new Sentence<Word>();
  for (Object obj : wList) {
    s.add(new Word(obj.toString()));
  }
  return s;
}
 

import edu.stanford.nlp.ling.Sentence; //导入方法依赖的package包/类
private static Sentence<Word> addLast(Sentence<Word> s) {
  Sentence<Word> s2 = new Sentence<Word>(s);
  //s2.add(new StringLabel(Lexicon.BOUNDARY));
  s2.add(new Word(Lexicon.BOUNDARY));
  return s2;
}