How to get NN andNNS from a text?

问题:

I want to get NN or NNS from a sample text as given within the script below. To this end, when I use the code below, the output is:

types
synchronization
phase
synchronization
-RSB-
synchronization
-LSB-
-RSB-
projection
synchronization

Here why am I getting [-RSB-] or [-LSB-]? Should I use a different pattern to get NN or NNS at the same time?

                atic = "So far, many different types of synchronization have been investigated, such as complete synchronization [8], generalized synchronization [9], phase synchronization [10], lag synchronization [11], projection synchronization [12, 13], and so forth.";

Reader reader = new StringReader(atic);
DocumentPreprocessor dp = new DocumentPreprocessor(reader);        
docs_terms_unq.put(rs.getString("u"), new ArrayList<String>());
docs_terms.put(rs.getString("u"), new ArrayList<String>());

for (List<HasWord> sentence : dp) {

List<TaggedWord> tagged = tagger.tagSentence(sentence);
GrammaticalStructure gs = parser.predict(tagged);


Tree x = parserr.parse(sentence); 
System.out.println(x);
TregexPattern NPpattern = TregexPattern.compile("@NN|NNS");
TregexMatcher matcher = NPpattern.matcher(x);


while (matcher.findNextMatchingNode()) {

Tree match = matcher.getMatch();
ArrayList hh = match.yield();    
Boolean b = false;

System.out.println(hh.toString());}

回答1:

I do not know why those are coming up. But you will get more accurate POS tags if you use the part of speech tagger. I would suggest just looking directly at the Annotation. Here is some sample code.

import edu.stanford.nlp.ling.CoreAnnotations;
import edu.stanford.nlp.ling.CoreLabel;
import edu.stanford.nlp.pipeline.Annotation;
import edu.stanford.nlp.pipeline.StanfordCoreNLP;
import edu.stanford.nlp.util.CoreMap;

import java.util.Properties;

public class NNExample {

    public static void main(String[] args) {
        Properties props = new Properties();
        props.setProperty("annotators", "tokenize,ssplit,pos");
        StanfordCoreNLP pipeline = new StanfordCoreNLP(props);
        String text = "So far, many different types of synchronization have been investigated, such as complete " +
                "synchronization [8], generalized synchronization [9], phase synchronization [10], " +
                "lag synchronization [11], projection synchronization [12, 13], and so forth.";
        Annotation annotation = new Annotation(text);
        pipeline.annotate(annotation);
        for (CoreMap sentence : annotation.get(CoreAnnotations.SentencesAnnotation.class)) {
            for (CoreLabel token : sentence.get(CoreAnnotations.TokensAnnotation.class)) {
                String partOfSpeechTag = token.get(CoreAnnotations.PartOfSpeechAnnotation.class);
                if (partOfSpeechTag.equals("NN") || partOfSpeechTag.equals("NNS")) {
                    System.out.println(token.word());
                }
            }
        }
    }
}

And the output I get.

types
synchronization
synchronization
synchronization
phase
synchronization
lag
synchronization
projection
synchronization

回答2:

Here is an example of getting the NP's from a sentence:

import edu.stanford.nlp.ling.CoreAnnotations;
import edu.stanford.nlp.ling.Word;
import edu.stanford.nlp.pipeline.Annotation;
import edu.stanford.nlp.pipeline.StanfordCoreNLP;
import edu.stanford.nlp.trees.*;

import java.io.IOException;
import java.util.ArrayList;
import java.util.Properties;

public class TreeExample {

    public static void printNounPhrases(Tree inputTree) {
        if (inputTree.label().value().equals("NP")) {
            ArrayList<Word> words = new ArrayList<Word>();
            for (Tree leaf : inputTree.getLeaves()) {
                words.addAll(leaf.yieldWords());
            }
            System.out.println(words);
        } else {
            for (Tree subTree : inputTree.children()) {
                printNounPhrases(subTree);
            }
        }
    }

    public static void main (String[] args) throws IOException {
        Properties props = new Properties();
        props.setProperty("annotators", "tokenize,ssplit,pos,lemma,ner,parse");
        StanfordCoreNLP pipeline = new StanfordCoreNLP(props);
        String text = "Susan Thompson is from Florida.";
        Annotation annotation = new Annotation(text);
        pipeline.annotate(annotation);
        Tree sentenceTree = annotation.get(CoreAnnotations.SentencesAnnotation.class).get(0).get(
                TreeCoreAnnotations.TreeAnnotation.class);
        //System.out.println(sentenceTree);
        printNounPhrases(sentenceTree);
    }

}