class_docstr: This class provides a wrapper of SpaCy of tokenizer, pos tagger and named entity recognizer
class_docstr_tok: ["This","class","provides","a","wrapper","of","SpaCy","of","tokenizer",",","pos","tagger","and","named","entity","recognizer"]
code: def sent_tokenize(self, doc):
      parsedData = self._nlp(doc)
      sent2str = lambda x: "".join(
          parsedData[i].string for i in range(x.start, x.end)
      ).strip()
      return map(sent2str, parsedData.sents)
  
imports: from sematch.utility import FileIO
  from nltk.stem import WordNetLemmatizer
  from nltk.corpus import wordnet
  import nltk
  from collections import Counter
  import itertools
  import string
  import re
label_desc: Use image node_id 2 for calling the SpaCyNLP obj's underlying member method code with example usage: obj.sent_tokenize(doc) and returns: map