'Initialize the indexes ``_lemma_to_class``,
``_wordnet_to_class``, and ``_class_to_fileid`` by scanning
through the corpus fileids.  This doesn\'t do proper xml parsing,
but is good enough to find everything in the standard verbnet
corpus -- and it runs about 30 times faster than xml parsing
(with the python ElementTree; only 2-3 times faster with
cElementTree).'

def _quick_index(self):

    for fileid in self._fileids:
        vnclass = fileid[:(-4)]
        self._class_to_fileid[vnclass] = fileid
        self._shortid_to_longid[self.shortid(vnclass)] = vnclass
        for m in self._INDEX_RE.finditer(self.open(fileid).read()):
            groups = m.groups()
            if (groups[0] is not None):
                self._lemma_to_class[groups[0]].append(vnclass)
                for wn in groups[1].split():
                    self._wordnet_to_class[wn].append(vnclass)
            elif (groups[2] is not None):
                self._class_to_fileid[groups[2]] = fileid
                vnclass = groups[2]
                self._shortid_to_longid[self.shortid(vnclass)] = vnclass
            else:
                assert False, u'unexpected    match    condition'
