code: def load(content):
      data = content.split("\n")
      headers = [row for row in data if row.startswith("# ")]
      headers = dict(
          [UDSentence._extract_header(content) for content in headers]
      )
      rows = [row for row in data if not row.startswith("# ")]
      rows = [r.split("\t") for r in rows]
      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 5 for calling the UDSentence obj's underlying member method code with example usage: obj.load(content) and returns: s