code: def __init__(
      self,
      language="zh",
      NAN="NAN",
      prefix="",
      template_path="configs/ner_template.json",
  ):
      self.language = language
      self.NAN = NAN
      self.prefix = prefix
  
      template = json.load(open(template_path, "r"))
      self.entity_template = template[language]["template"]
      self.entity_open_template = template[language]["open_template"]
  
      self.entity_int_out_format_zh = {
          0: ["(实体,实体类型)\n", self.entity_convert_target0],
          1: ["实体是,实体类型是\n", self.entity_convert_target1],
          2: ["实体类型：实体\n", self.entity_convert_target2],
          3: [
              "{'entity':'', 'entity_type':''}\n",
              self.entity_convert_target3,
          ],
      }
      self.entity_int_out_format_en = {
          0: ["(Entity,Entity Type)\n", self.entity_convert_target0],
          1: [
              "Entity is,Entity Type is\n",
              self.entity_convert_target1_en,
          ],
          2: ["Entity Type：Entity\n", self.entity_convert_target2],
          3: [
              "{'entity':'', 'entity_type':''}\n",
              self.entity_convert_target3,
          ],
      }
  
      if language == "zh":
          self.entity_int_out_format = self.entity_int_out_format_zh
      else:
          self.entity_int_out_format = self.entity_int_out_format_en
  
file_path: DeepKE/example/llm/InstructKGC/kg2instruction/convert/converter/ner_converter.py
imports: import json
label_desc: Use image node_id 1 to create a new NERConverter object  with example: obj = NERConverter(language, NAN, prefix, template_path)