docs: def convertCONLLtoText( in_file, addDepRels = False, verbose = False, **kwargs ):
      ''' Loads CONLL format data from given input file, and creates
          estnltk Text objects from the data, one Text per each 
          sentence. Returns a list of Text objects.
          
          By default, applies estnltk's morphological analysis, clause 
          detection, and verb chain detection to each input sentence.
          
          If addDepRels == True, in addition to SYNTAX_LABEL and SYNTAX_HEAD,
          surface syntactic function (DEPREL) is also attributed to each 
          token;
      '''
      from estnltk.text import Text
      sentences = loadCONLLannotations( in_file, addDepRels = addDepRels, \
                                                 splitIntoSentences = True )
      if verbose:
          print( str(len(sentences))+' sentences loaded. ')
      estnltkSentTexts = []
      for i in range(len(sentences)):
          s  = sentences[i]
          sentenceString = " ".join( [ t[2] for t in s ] )
          sentText = Text(sentenceString, **kwargs)
          sentText.tag_analysis()
          sentText.tag_clauses()
          sentText.tag_verb_chains()
          sentText = dict(sentText)
          if len(sentText[WORDS]) == len(s):
              # Add the dependency syntactic information
              for j in range(len(sentText[WORDS])):
                  estnltkWord   = sentText[WORDS][j]
                  depSyntaxWord = s[j]
                  estnltkWord[SYNTAX_LABEL] = depSyntaxWord[4]
                  estnltkWord[SYNTAX_HEAD]  = depSyntaxWord[5]
                  if addDepRels:
                     estnltkWord[DEPREL] = depSyntaxWord[6]
              estnltkSentTexts.append( sentText )
              if verbose:
                  print ('*', end = '')
          else:
              if verbose:
                  print("The sentence segmentation of dependency syntax differs from the estnltk's sentence segmentation:", len(sentText[WORDS]), ' vs ',len(s))
      return estnltkSentTexts