Question

我想用Stanford NLP解析器解析句子列表。我的列表是ArrayList，如何使用LexicalizedParser解析所有列表？

我想从每个句子中得到这种形式：

Tree parse =  (Tree) lp1.apply(sentence);

Answer 1

虽然可以深入研究文档，但我将在此处提供代码，特别是因为链接移动和/或死亡。这个特定的答案使用整个管道。如果对整个管道不感兴趣，我会在一秒钟内提供一个替代答案。

以下示例是使用斯坦福管道的完整方式。如果对共参考分辨率不感兴趣，请从第3行代码中删除dcoref。因此，在下面的示例中，如果您只是在文本体（文本变量）中提供它，那么管道会为您（ssplit注释器）执行句子分割。只有一句话？好吧，没关系，您可以将其作为文本变量提供。

   // creates a StanfordCoreNLP object, with POS tagging, lemmatization, NER, parsing, and coreference resolution 
    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 = ... // Add your text here!

    // 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 2

实际上，斯坦福大学NLP的文档提供了如何解析句子的样本。

您可以找到文档here

Answer 3

正如所承诺的那样，如果您不想访问完整的斯坦福管道（虽然我认为这是推荐的方法），您可以直接使用LexicalizedParser类。在这种情况下，您将下载最新版本的Stanford Parser（而另一个则使用CoreNLP工具）。除了解析器jar之外，还要确保您具有要使用的相应解析器的模型文件。示例代码：

LexicalizedParser lp1 = new LexicalizedParser("englishPCFG.ser.gz", new Options());
String sentence = "It is a fine day today";
Tree parse = lp.parse(sentence);

注意这适用于解析器的3.3.1版。

如何解析句子列表？

3 个答案: