斯坦福核心 nlp java 输出

Question

我是 Java 和斯坦福 NLP 工具包的新手，并试图将它们用于项目。具体来说，我正在尝试使用 Stanford Corenlp 工具包来注释文本（使用 Netbeans 而不是命令行）并且我尝试使用 http://nlp.stanford.edu/software/corenlp.shtml#Usage 上提供的代码（使用 Stanford CoreNLP API）.. 问题是：谁能告诉我如何在文件中获取输出以便进一步处理它？

我尝试将图形和句子打印到控制台，只是为了查看内容。这样可行。基本上我需要的是返回带注释的文档，这样我就可以从我的主类中调用它并输出一个文本文件（如果可能的话）。我正在尝试查看 stanford corenlp 的 API，但鉴于我缺乏经验，我真的不知道返回此类信息的最佳方式是什么。

代码如下：

Properties props = new Properties();
    props.put("annotators", "tokenize, ssplit, pos, lemma, ner, parse, dcoref");
    StanfordCoreNLP pipeline = new StanfordCoreNLP(props);

    // read some text in the text variable
    String text = "the quick fox jumps over the lazy dog";

    // create an empty Annotation just with the given text
    Annotation document = new Annotation(text);

    // run all Annotators on this text
    pipeline.annotate(document);

    // these are all the sentences in this document
    // a CoreMap is essentially a Map that uses class objects as keys and has values with custom types
    List<CoreMap> sentences = document.get(SentencesAnnotation.class);

    for(CoreMap sentence: sentences) {
      // traversing the words in the current sentence
      // a CoreLabel is a CoreMap with additional token-specific methods
      for (CoreLabel token: sentence.get(TokensAnnotation.class)) {
        // this is the text of the token
        String word = token.get(TextAnnotation.class);
        // this is the POS tag of the token
        String pos = token.get(PartOfSpeechAnnotation.class);
        // this is the NER label of the token
        String ne = token.get(NamedEntityTagAnnotation.class);       
      }

      // this is the parse tree of the current sentence
      Tree tree = sentence.get(TreeAnnotation.class);

      // this is the Stanford dependency graph of the current sentence
      SemanticGraph dependencies = sentence.get(CollapsedCCProcessedDependenciesAnnotation.class);
    }

    // This is the coreference link graph
    // Each chain stores a set of mentions that link to each other,
    // along with a method for getting the most representative mention
    // Both sentence and token offsets start at 1!
    Map<Integer, CorefChain> graph = 
      document.get(CorefChainAnnotation.class);

Answer 1

一旦您的代码示例中显示了任何或所有自然语言分析，您所需要做的就是以正常的 Java 方式将它们发送到文件中，例如，使用 FileWriter 进行文本格式输出。具体来说，这是一个简单的完整示例，显示发送到文件的输出（如果您为其提供适当的命令行参数）：

import java.io.*;
import java.util.*;

import edu.stanford.nlp.io.*;
import edu.stanford.nlp.ling.*;
import edu.stanford.nlp.pipeline.*;
import edu.stanford.nlp.trees.*;
import edu.stanford.nlp.util.*;

public class StanfordCoreNlpDemo {

  public static void main(String[] args) throws IOException {
    PrintWriter out;
    if (args.length > 1) {
      out = new PrintWriter(args[1]);
    } else {
      out = new PrintWriter(System.out);
    }
    PrintWriter xmlOut = null;
    if (args.length > 2) {
      xmlOut = new PrintWriter(args[2]);
    }

    StanfordCoreNLP pipeline = new StanfordCoreNLP();
    Annotation annotation;
    if (args.length > 0) {
      annotation = new Annotation(IOUtils.slurpFileNoExceptions(args[0]));
    } else {
      annotation = new Annotation("Kosgi Santosh sent an email to Stanford University. He didn't get a reply.");
    }

    pipeline.annotate(annotation);
    pipeline.prettyPrint(annotation, out);
    if (xmlOut != null) {
      pipeline.xmlPrint(annotation, xmlOut);
    }
    // An Annotation is a Map and you can get and use the various analyses individually.
    // For instance, this gets the parse tree of the first sentence in the text.
    List<CoreMap> sentences = annotation.get(CoreAnnotations.SentencesAnnotation.class);
    if (sentences != null && sentences.size() > 0) {
      CoreMap sentence = sentences.get(0);
      Tree tree = sentence.get(TreeCoreAnnotations.TreeAnnotation.class);
      out.println();
      out.println("The first sentence parsed is:");
      tree.pennPrint(out);
    }
  }

}