172 lines
4.8 KiB
Python
172 lines
4.8 KiB
Python
#
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# Copyright (C) 2001-2019 NLTK Project
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# Author: Masato Hagiwara <hagisan@gmail.com>
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# URL: <http://nltk.org/>
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# For license information, see LICENSE.TXT
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# For more information, see http://lilyx.net/pages/nltkjapanesecorpus.html
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from __future__ import print_function
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import sys
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from six import string_types
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from nltk.corpus.reader import util
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from nltk.corpus.reader.util import *
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from nltk.corpus.reader.api import *
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class ChasenCorpusReader(CorpusReader):
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def __init__(self, root, fileids, encoding='utf8', sent_splitter=None):
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self._sent_splitter = sent_splitter
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CorpusReader.__init__(self, root, fileids, encoding)
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def raw(self, fileids=None):
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if fileids is None:
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fileids = self._fileids
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elif isinstance(fileids, string_types):
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fileids = [fileids]
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return concat([self.open(f).read() for f in fileids])
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def words(self, fileids=None):
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return concat(
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[
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ChasenCorpusView(fileid, enc, False, False, False, self._sent_splitter)
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for (fileid, enc) in self.abspaths(fileids, True)
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]
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)
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def tagged_words(self, fileids=None):
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return concat(
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[
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ChasenCorpusView(fileid, enc, True, False, False, self._sent_splitter)
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for (fileid, enc) in self.abspaths(fileids, True)
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]
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)
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def sents(self, fileids=None):
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return concat(
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[
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ChasenCorpusView(fileid, enc, False, True, False, self._sent_splitter)
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for (fileid, enc) in self.abspaths(fileids, True)
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]
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)
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def tagged_sents(self, fileids=None):
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return concat(
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[
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ChasenCorpusView(fileid, enc, True, True, False, self._sent_splitter)
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for (fileid, enc) in self.abspaths(fileids, True)
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]
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)
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def paras(self, fileids=None):
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return concat(
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[
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ChasenCorpusView(fileid, enc, False, True, True, self._sent_splitter)
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for (fileid, enc) in self.abspaths(fileids, True)
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]
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)
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def tagged_paras(self, fileids=None):
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return concat(
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[
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ChasenCorpusView(fileid, enc, True, True, True, self._sent_splitter)
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for (fileid, enc) in self.abspaths(fileids, True)
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]
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)
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class ChasenCorpusView(StreamBackedCorpusView):
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"""
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A specialized corpus view for ChasenReader. Similar to ``TaggedCorpusView``,
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but this'll use fixed sets of word and sentence tokenizer.
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"""
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def __init__(
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self,
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corpus_file,
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encoding,
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tagged,
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group_by_sent,
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group_by_para,
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sent_splitter=None,
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):
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self._tagged = tagged
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self._group_by_sent = group_by_sent
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self._group_by_para = group_by_para
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self._sent_splitter = sent_splitter
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StreamBackedCorpusView.__init__(self, corpus_file, encoding=encoding)
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def read_block(self, stream):
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"""Reads one paragraph at a time."""
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block = []
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for para_str in read_regexp_block(stream, r".", r"^EOS\n"):
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para = []
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sent = []
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for line in para_str.splitlines():
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_eos = line.strip() == 'EOS'
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_cells = line.split('\t')
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w = (_cells[0], '\t'.join(_cells[1:]))
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if not _eos:
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sent.append(w)
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if _eos or (self._sent_splitter and self._sent_splitter(w)):
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if not self._tagged:
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sent = [w for (w, t) in sent]
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if self._group_by_sent:
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para.append(sent)
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else:
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para.extend(sent)
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sent = []
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if len(sent) > 0:
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if not self._tagged:
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sent = [w for (w, t) in sent]
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if self._group_by_sent:
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para.append(sent)
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else:
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para.extend(sent)
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if self._group_by_para:
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block.append(para)
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else:
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block.extend(para)
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return block
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def demo():
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import nltk
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from nltk.corpus.util import LazyCorpusLoader
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jeita = LazyCorpusLoader('jeita', ChasenCorpusReader, r'.*chasen', encoding='utf-8')
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print('/'.join(jeita.words()[22100:22140]))
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print(
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'\nEOS\n'.join(
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'\n'.join("%s/%s" % (w[0], w[1].split('\t')[2]) for w in sent)
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for sent in jeita.tagged_sents()[2170:2173]
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)
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)
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def test():
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from nltk.corpus.util import LazyCorpusLoader
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jeita = LazyCorpusLoader('jeita', ChasenCorpusReader, r'.*chasen', encoding='utf-8')
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assert isinstance(jeita.tagged_words()[0][1], string_types)
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if __name__ == '__main__':
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demo()
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test()
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