# Natural Language Toolkit: NPS Chat Corpus Reader # # Copyright (C) 2001-2017 NLTK Project # Author: Edward Loper # URL: # For license information, see LICENSE.TXT from __future__ import unicode_literals import re import textwrap from nltk.util import LazyConcatenation from nltk.internals import ElementWrapper from nltk.tag import map_tag from nltk.corpus.reader.util import * from nltk.corpus.reader.api import * from nltk.corpus.reader.xmldocs import * class NPSChatCorpusReader(XMLCorpusReader): def __init__(self, root, fileids, wrap_etree=False, tagset=None): XMLCorpusReader.__init__(self, root, fileids, wrap_etree) self._tagset = tagset def xml_posts(self, fileids=None): if self._wrap_etree: return concat([XMLCorpusView(fileid, 'Session/Posts/Post', self._wrap_elt) for fileid in self.abspaths(fileids)]) else: return concat([XMLCorpusView(fileid, 'Session/Posts/Post') for fileid in self.abspaths(fileids)]) def posts(self, fileids=None): return concat([XMLCorpusView(fileid, 'Session/Posts/Post/terminals', self._elt_to_words) for fileid in self.abspaths(fileids)]) def tagged_posts(self, fileids=None, tagset=None): def reader(elt, handler): return self._elt_to_tagged_words(elt, handler, tagset) return concat([XMLCorpusView(fileid, 'Session/Posts/Post/terminals', reader) for fileid in self.abspaths(fileids)]) def words(self, fileids=None): return LazyConcatenation(self.posts(fileids)) def tagged_words(self, fileids=None, tagset=None): return LazyConcatenation(self.tagged_posts(fileids, tagset)) def _wrap_elt(self, elt, handler): return ElementWrapper(elt) def _elt_to_words(self, elt, handler): return [self._simplify_username(t.attrib['word']) for t in elt.findall('t')] def _elt_to_tagged_words(self, elt, handler, tagset=None): tagged_post = [(self._simplify_username(t.attrib['word']), t.attrib['pos']) for t in elt.findall('t')] if tagset and tagset != self._tagset: tagged_post = [(w, map_tag(self._tagset, tagset, t)) for (w, t) in tagged_post] return tagged_post @staticmethod def _simplify_username(word): if 'User' in word: word = 'U' + word.split('User', 1)[1] elif isinstance(word, bytes): word = word.decode('ascii') return word