class_docstr: A processing interface for identifying non-overlapping groups in
  unrestricted text.  Typically, chunk parsers are used to find base
  syntactic constituents, such as base noun phrases.  Unlike
  ``ParserI``, ``ChunkParserI`` guarantees that the ``parse()`` method
  will always generate a parse.
docstr: Return the best chunk structure for the given tokens
  and return a tree.
  
  :param tokens: The list of (word, tag) tokens to be chunked.
  :type tokens: list(tuple)
  :rtype: Tree
docstr_tok: ["Return","the","best","chunk","structure","for","the","given","tokens","and","return","a","tree",".",":","param","tokens",":","The","list","of","(","word",",","tag",")","tokens","to","be","chunked",".",":","type","tokens",":","list","(","tuple",")",":","rtype",":","Tree"]
code: def parse(self, tokens):
      """
      Return the best chunk structure for the given tokens
      and return a tree.
  
      :param tokens: The list of (word, tag) tokens to be chunked.
      :type tokens: list(tuple)
      :rtype: Tree
      """
      raise NotImplementedError()
  
file_path: nltk/nltk/chunk/api.py
imports: from nltk.chunk.util import ChunkScore
  from nltk.internals import deprecated
  from nltk.parse import ParserI
label_desc: Use image node_id 1 for calling the ChunkParserI obj's underlying member method code with example usage: obj.parse(tokens) without return types