本文介绍了如何从文本中获取NN和NNS?的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我想从下面的脚本中给出的示例文本中获取NN或NNS.为此,当我使用下面的代码时,输​​出为:

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

为什么我会得到[-RSB-][-LSB-]?我是否应该使用其他模式同时获取NN或NNS?

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());}

推荐答案

我不知道为什么会出现这些问题.但是,如果您使用语音标记器,您将获得更准确的POS标记.我建议直接看一下注解.这是一些示例代码.

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());
                }
            }
        }
    }
}

还有我得到的输出.

types
synchronization
synchronization
synchronization
phase
synchronization
lag
synchronization
projection
synchronization

这篇关于如何从文本中获取NN和NNS?的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!

09-05 13:07
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