code: private void loadServerParameters() {
      serverParser.addArgument("-p", "--port").required(true)
          .help("Port to be assigned to the server.\n");
      serverParser.addArgument("-m", "--model").required(true)
          .help("Pass the model to do the tagging as a parameter.\n");
      serverParser.addArgument("--clearFeatures").required(false)
          .choices("yes", "no", "docstart").setDefault(Flags.DEFAULT_FEATURE_FLAG)
          .help(
              "Reset the adaptive features every sentence; defaults to 'no'; if -DOCSTART- marks"
                  + " are present, choose 'docstart'.\n");
      serverParser
          .addArgument("-l", "--language").required(true).choices("ca", "de",
              "en", "es", "eu", "fr", "gl", "it", "nl", "pt", "ru")
          .help("Choose language.\n");
      serverParser.addArgument("-o", "--outputFormat").required(false)
          .choices("conll03", "conll02", "naf")
          .setDefault(Flags.DEFAULT_OUTPUT_FORMAT)
          .help("Choose output format; it defaults to NAF.\n");
      serverParser.addArgument("--lexer").choices("numeric")
          .setDefault(Flags.DEFAULT_LEXER).required(false)
          .help("Use lexer rules for NERC tagging; it defaults to false.\n");
      serverParser.addArgument("--dictTag").required(false).choices("tag", "post")
          .setDefault(Flags.DEFAULT_DICT_OPTION).help(
              "Choose to directly tag entities by dictionary look-up; if the 'tag' option is chosen, "
                  + "only tags entities found in the dictionary; if 'post' option is chosen, it will "
                  + "post-process the results of the statistical model.\n");
      serverParser.addArgument("--dictPath").required(false)
          .setDefault(Flags.DEFAULT_DICT_PATH).help(
              "Provide the path to the dictionaries for direct dictionary tagging; it ONLY WORKS if --dictTag "
                  + "option is activated.\n");
    }
docs: Create the available parameters for NER tagging.