# Natural Language Toolkit: Indian Language POS-Tagged Corpus Reader
#
# Copyright (C) 2001-2023 NLTK Project
# Author: Steven Bird <stevenbird1@gmail.com>
# Edward Loper <edloper@gmail.com>
# URL: <https://www.nltk.org/>
# For license information, see LICENSE.TXT
"""
Indian Language POS-Tagged Corpus
Collected by A Kumaran, Microsoft Research, India
Distributed with permission
Contents:
- Bangla: IIT Kharagpur
- Hindi: Microsoft Research India
- Marathi: IIT Bombay
- Telugu: IIIT Hyderabad
"""
from nltk.corpus.reader.api import *
from nltk.corpus.reader.util import *
from nltk.tag import map_tag, str2tuple
[docs]class IndianCorpusReader(CorpusReader):
"""
List of words, one per line. Blank lines are ignored.
"""
[docs] def words(self, fileids=None):
return concat(
[
IndianCorpusView(fileid, enc, False, False)
for (fileid, enc) in self.abspaths(fileids, True)
]
)
[docs] def tagged_words(self, fileids=None, tagset=None):
if tagset and tagset != self._tagset:
tag_mapping_function = lambda t: map_tag(self._tagset, tagset, t)
else:
tag_mapping_function = None
return concat(
[
IndianCorpusView(fileid, enc, True, False, tag_mapping_function)
for (fileid, enc) in self.abspaths(fileids, True)
]
)
[docs] def sents(self, fileids=None):
return concat(
[
IndianCorpusView(fileid, enc, False, True)
for (fileid, enc) in self.abspaths(fileids, True)
]
)
[docs] def tagged_sents(self, fileids=None, tagset=None):
if tagset and tagset != self._tagset:
tag_mapping_function = lambda t: map_tag(self._tagset, tagset, t)
else:
tag_mapping_function = None
return concat(
[
IndianCorpusView(fileid, enc, True, True, tag_mapping_function)
for (fileid, enc) in self.abspaths(fileids, True)
]
)
[docs]class IndianCorpusView(StreamBackedCorpusView):
[docs] def __init__(
self, corpus_file, encoding, tagged, group_by_sent, tag_mapping_function=None
):
self._tagged = tagged
self._group_by_sent = group_by_sent
self._tag_mapping_function = tag_mapping_function
StreamBackedCorpusView.__init__(self, corpus_file, encoding=encoding)
[docs] def read_block(self, stream):
line = stream.readline()
if line.startswith("<"):
return []
sent = [str2tuple(word, sep="_") for word in line.split()]
if self._tag_mapping_function:
sent = [(w, self._tag_mapping_function(t)) for (w, t) in sent]
if not self._tagged:
sent = [w for (w, t) in sent]
if self._group_by_sent:
return [sent]
else:
return sent