class_docstr: An NLTK interface to the VerbNet verb lexicon.
  
  From the VerbNet site: "VerbNet (VN) (Kipper-Schuler 2006) is the largest
  on-line verb lexicon currently available for English. It is a hierarchical
  domain-independent, broad-coverage verb lexicon with mappings to other
  lexical resources such as WordNet (Miller, 1990; Fellbaum, 1998), XTAG
  (XTAG Research Group, 2001), and FrameNet (Baker et al., 1998)."
  
  For details about VerbNet see:
  https://verbs.colorado.edu/~mpalmer/projects/verbnet.html
class_docstr_tok: ["An","NLTK","interface","to","the","VerbNet","verb","lexicon",".","From","the","VerbNet","site",":","``","VerbNet","(","VN",")","(","Kipper-Schuler","2006",")","is","the","largest","on-line","verb","lexicon","currently","available","for","English",".","It","is","a","hierarchical","domain-independent",",","broad-coverage","verb","lexicon","with","mappings","to","other","lexical","resources","such","as","WordNet","(","Miller",",","1990",";","Fellbaum",",","1998",")",",","XTAG","(","XTAG","Research","Group",",","2001",")",",","and","FrameNet","(","Baker","et","al.",",","1998",")",".","''","For","details","about","VerbNet","see",":","https",":","\/\/verbs.colorado.edu\/~mpalmer\/projects\/verbnet.html"]
code: def __init__(self, root, fileids, wrap_etree=False):
      XMLCorpusReader.__init__(self, root, fileids, wrap_etree)
  
      self._lemma_to_class = defaultdict(list)
      """A dictionary mapping from verb lemma strings to lists of
          VerbNet class identifiers."""
  
      self._wordnet_to_class = defaultdict(list)
      """A dictionary mapping from wordnet identifier strings to
          lists of VerbNet class identifiers."""
  
      self._class_to_fileid = {}
      """A dictionary mapping from class identifiers to
          corresponding file identifiers.  The keys of this dictionary
          provide a complete list of all classes and subclasses."""
  
      self._shortid_to_longid = {}
  
      # Initialize the dictionaries.  Use the quick (regexp-based)
      # method instead of the slow (xml-based) method, because it
      # runs 2-30 times faster.
      self._quick_index()
  
imports: import re
  import textwrap
  from collections import defaultdict
  from nltk.corpus.reader.xmldocs import XMLCorpusReader
label_desc: Use image node_id 1 to create a new VerbnetCorpusReader object from inherited base classes: XMLCorpusReader with example: obj = VerbnetCorpusReader(root, fileids, wrap_etree)