Question

我正在使用Stanford NLP来生成解析文档树。然后，我想迭代这些文档，并存储长度为2或3个字的所有短语，这些短语是VP（动词短语）或NP（名词短语）的一部分。我可以用什么策略来实现这个目标？

Answer 1

以下是一些示例代码，它将通过树并打印出NP和VP中的单词：

package edu.stanford.nlp.examples;

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

import java.util.*;

public class ConstituentExample {

  public static void main(String[] args) {
    // set up pipeline properties
    Properties props = new Properties();
    props.setProperty("annotators", "tokenize,ssplit,pos,lemma,ner,parse");
    // use faster shift reduce parser
    props.setProperty("parse.model", "edu/stanford/nlp/models/srparser/englishSR.ser.gz");
    props.setProperty("parse.maxlen", "100");
    // set up Stanford CoreNLP pipeline
    StanfordCoreNLP pipeline = new StanfordCoreNLP(props);
    // build annotation for a review
    Annotation annotation =
        new Annotation("The small red car turned very quickly around the corner.");
    // annotate
    pipeline.annotate(annotation);
    // get tree
    Tree tree =
        annotation.get(CoreAnnotations.SentencesAnnotation.class).get(0).get(TreeCoreAnnotations.TreeAnnotation.class);
    System.out.println(tree);
    Set<Constituent> treeConstituents = tree.constituents(new LabeledScoredConstituentFactory());
    for (Constituent constituent : treeConstituents) {
      if (constituent.label() != null &&
          (constituent.label().toString().equals("VP") || constituent.label().toString().equals("NP"))) {
        System.err.println("found constituent: "+constituent.toString());
        System.err.println(tree.getLeaves().subList(constituent.start(), constituent.end()+1));
      }
    }
  }
}

如何让所有拥有2或3个直接孩子的VP和NP

1 个答案: