code: public static void recognition(List<Vertex> segResult, WordNet wordNetOptimum, WordNet wordNetAll)
      {
          StringBuilder sbName = new StringBuilder();
          int appendTimes = 0;
          ListIterator<Vertex> listIterator = segResult.listIterator();
          listIterator.next();
          int line = 1;
          int activeLine = 1;
          while (listIterator.hasNext())
          {
              Vertex vertex = listIterator.next();
              if (appendTimes > 0)
              {
                  if (vertex.guessNature() == Nature.nrf || TranslatedPersonDictionary.containsKey(vertex.realWord))
                  {
                      sbName.append(vertex.realWord);
                      ++appendTimes;
                  }
                  else
                  {
                      // 识别结束
                      if (appendTimes > 1)
                      {
                          if (HanLP.Config.DEBUG)
                          {
                              System.out.println("音译人名识别出：" + sbName.toString());
                          }
                          wordNetOptimum.insert(activeLine, new Vertex(Predefine.TAG_PEOPLE, sbName.toString(), new CoreDictionary.Attribute(Nature.nrf), WORD_ID), wordNetAll);
                      }
                      sbName.setLength(0);
                      appendTimes = 0;
                  }
              }
              else
              {
                  // nrf触发识别
                  if (vertex.guessNature() == Nature.nrf
  //                        || TranslatedPersonDictionary.containsKey(vertex.realWord)
                          )
                  {
                      sbName.append(vertex.realWord);
                      ++appendTimes;
                      activeLine = line;
                  }
              }
  
              line += vertex.realWord.length();
          }
      }
docs: 执行识别
  @param segResult 粗分结果
  @param wordNetOptimum 粗分结果对应的词图
  @param wordNetAll 全词图