斯坦福核心 nlp java 输出

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，我试图使用Stanford Corenlp工具包来注释文本（使用Netbeans而不是命令行），并且我试图使用 http://nlp.stanford.edu/software/corenlp.shtml#Usage（使用Stanford CoreNLP API）上提供的代码。问题是：任何人都可以告诉我如何获取文件中的输出，以便我可以进一步处理它？

我尝试将图表和句子打印到控制台，只是为了查看内容。这行得通。基本上，我需要的是返回带注释的文档，以便我可以从主类调用它并输出文本文件（如果可能的话）。我试图查看斯坦福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);