code: def load_from_raw_content(raw_content):
      sentences = raw_content.split("\n")
      headers = sentences[:3]
      headers = dict([UDSentence._extract_header(_) for _ in headers])
      text = sentences[-1]
      headers["text"] = text
      headers["type"] = "bronze"
      headers["authors"] = BOT_VERSION
      pos_tags = pos_tag(text)
      dp_tags = dependency_parse(text)
      rows = [
          (item[0][0], item[0][1], str(item[1][1]), item[1][2])
          for item in zip(pos_tags, dp_tags)
      ]
      s = UDSentence(rows=rows, headers=headers)
      return s
  
imports: from os.path import dirname, join, exists
  from torch.utils.data import Dataset
  from underthesea import pos_tag
  from underthesea import dependency_parse
  from underthesea.utils.col_analyzer import UDAnalyzer
label_desc: Use image node_id 6 for calling the UDSentence obj's underlying member method code with example usage: obj.load_from_raw_content(raw_content) and returns: s