Stanford Core NLP - 了解共同参与解决方案

3 回答

• 8

  我一直在使用coreference依赖图，我开始使用这个问题的另一个答案 . 过了一会儿，虽然我意识到上面这个算法并不完全正确 . 它产生的输出甚至不接近我的修改版本 .

  对于使用这篇文章的任何人来说，这里是我最终得到的算法，它也过滤掉了自引用，因为每个代表性的人都会提到自己，很多提到只引用自己 .

  Map<Integer, CorefChain> coref = document.get(CorefChainAnnotation.class);
  
  for(Map.Entry<Integer, CorefChain> entry : coref.entrySet()) {
      CorefChain c = entry.getValue();
  
      //this is because it prints out a lot of self references which aren't that useful
      if(c.getCorefMentions().size() <= 1)
          continue;
  
      CorefMention cm = c.getRepresentativeMention();
      String clust = "";
      List<CoreLabel> tks = document.get(SentencesAnnotation.class).get(cm.sentNum-1).get(TokensAnnotation.class);
      for(int i = cm.startIndex-1; i < cm.endIndex-1; i++)
          clust += tks.get(i).get(TextAnnotation.class) + " ";
      clust = clust.trim();
      System.out.println("representative mention: \"" + clust + "\" is mentioned by:");
  
      for(CorefMention m : c.getCorefMentions()){
          String clust2 = "";
          tks = document.get(SentencesAnnotation.class).get(m.sentNum-1).get(TokensAnnotation.class);
          for(int i = m.startIndex-1; i < m.endIndex-1; i++)
              clust2 += tks.get(i).get(TextAnnotation.class) + " ";
          clust2 = clust2.trim();
          //don't need the self mention
          if(clust.equals(clust2))
              continue;
  
          System.out.println("\t" + clust2);
      }
  }
  

  您的例句的最终输出如下：

  representative mention: "a basic unit of matter" is mentioned by:
  The atom
  it
  

  通常“原子”最终成为代表性的提及，但在这种情况下它并不令人惊讶 . 输出稍微更精确的另一个例子是以下句子：

  革命战争发生在18世纪，这是美国的第一次战争 .

  产生以下输出：

  representative mention: "The Revolutionary War" is mentioned by:
  it
  the first war in the United States
  

  回复于 2024-05-02T10:21:54+08:00
• 17

  这些是注释者最近的结果 .

  • [1,1] 1原子

  • [1,2] 1是一个基本的物质单位

  • [1,3] 1它

  • [1,6] 6个带负电荷的电子

  • [1,5] 5带负电的电子 Cloud

  标记如下：

  [Sentence number,'id']  Cluster_no  Text_Associated
  

  属于同一群集的文本指的是相同的上下文 .

  回复于 2024-05-02T10:21:54+08:00
• 0

  第一个数字是一个集群ID（代表标记，代表同一个实体），参见 SieveCoreferenceSystem#coref(Document) 的源代码 . 对数字不在CorefChain＃toString（）中：

  public String toString(){
      return position.toString();
  }
  

  其中position是一组提到实体的位置对（让他们使用 CorefChain.getCorefMentions() ） . 以下是完整代码的示例（在groovy中），其中显示了如何从位置到令牌：

  class Example {
      public static void main(String[] args) {
          Properties props = new Properties();
          props.put("annotators", "tokenize, ssplit, pos, lemma, ner, parse, dcoref");
          props.put("dcoref.score", true);
          pipeline = new StanfordCoreNLP(props);
          Annotation document = new Annotation("The atom is a basic unit of matter, it   consists of a dense central nucleus surrounded by a cloud of negatively charged electrons.");
  
          pipeline.annotate(document);
          Map<Integer, CorefChain> graph = document.get(CorefChainAnnotation.class);
  
          println aText
  
          for(Map.Entry<Integer, CorefChain> entry : graph) {
            CorefChain c =   entry.getValue();                
            println "ClusterId: " + entry.getKey();
            CorefMention cm = c.getRepresentativeMention();
            println "Representative Mention: " + aText.subSequence(cm.startIndex, cm.endIndex);
  
            List<CorefMention> cms = c.getCorefMentions();
            println  "Mentions:  ";
            cms.each { it -> 
                print aText.subSequence(it.startIndex, it.endIndex) + "|"; 
            }         
          }
      }
  }
  

  输出（我不明白's'来自哪里）：

  The atom is a basic unit of matter, it consists of a dense central nucleus surrounded by a cloud of negatively charged electrons.
  ClusterId: 1
  Representative Mention: he
  Mentions: he|atom |s|
  ClusterId: 6
  Representative Mention:  basic unit 
  Mentions:  basic unit |
  ClusterId: 8
  Representative Mention:  unit 
  Mentions:  unit |
  ClusterId: 10
  Representative Mention: it 
  Mentions: it |
  

  回复于 2024-05-02T10:21:54+08:00