class_docstr: Return a stemmed Arabic word after removing affixes. This an improved
  version of the previous algorithm, which reduces under-stemming errors.
  Typically used in Arabic search engine, information retrieval and NLP.
  
      >>> from nltk.stem import arlstem2
      >>> stemmer = ARLSTem2()
      >>> word = stemmer.stem('يعمل')
      >>> print(word)
      عمل
  
  :param token: The input Arabic word (unicode) to be stemmed
  :type token: unicode
  :return: A unicode Arabic word
class_docstr_tok: ["Return","a","stemmed","Arabic","word","after","removing","affixes",".","This","an","improved","version","of","the","previous","algorithm",",","which","reduces","under-stemming","errors",".","Typically","used","in","Arabic","search","engine",",","information","retrieval","and","NLP",".",">",">",">","from","nltk.stem","import","arlstem2",">",">",">","stemmer","=","ARLSTem2","(",")",">",">",">","word","=","stemmer.stem","(","'\u064a\u0639\u0645\u0644","'",")",">",">",">","print","(","word",")","\u0639\u0645\u0644",":","param","token",":","The","input","Arabic","word","(","unicode",")","to","be","stemmed",":","type","token",":","unicode",":","return",":","A","unicode","Arabic","word"]
docstr: stem the present tense co-occurred prefixes and suffixes
docstr_tok: ["stem","the","present","tense","co-occurred","prefixes","and","suffixes"]
code: def verb_t1(self, token):
      """
      stem the present tense co-occurred prefixes and suffixes
      """
      if len(token) > 5 and token.startswith("\u062A"):  # Taa
          for s2 in self.pl_si2:
              if token.endswith(s2):
                  return token[1:-2]
      if len(token) > 5 and token.startswith("\u064A"):  # Yaa
          for s2 in self.verb_su2:
              if token.endswith(s2):
                  return token[1:-2]
      if len(token) > 4 and token.startswith("\u0627"):  # Alif
          # Waaw Alif
          if len(token) > 5 and token.endswith("\u0648\u0627"):
              return token[1:-2]
          # Yaa
          if token.endswith("\u064A"):
              return token[1:-1]
          # Alif
          if token.endswith("\u0627"):
              return token[1:-1]
          # Noon
          if token.endswith("\u0646"):
              return token[1:-1]
      # ^Yaa, Noon$
      if (
          len(token) > 4
          and token.startswith("\u064A")
          and token.endswith("\u0646")
      ):
          return token[1:-1]
      # ^Taa, Noon$
      if (
          len(token) > 4
          and token.startswith("\u062A")
          and token.endswith("\u0646")
      ):
          return token[1:-1]
  
imports: import re
  from nltk.stem.api import StemmerI
label_desc: Use image node_id 11 for calling the ARLSTem2 obj's underlying member method code with example usage: obj.verb_t1(token) and returns: token, token, token, token, token, token, token, token