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# Natural Language Toolkit: PP Attachment Corpus Reader
#
# Copyright (C) 2001-2023 NLTK Project
# Author: Steven Bird <[email protected]>
# Edward Loper <[email protected]>
# URL: <https://www.nltk.org/>
# For license information, see LICENSE.TXT
"""
Read lines from the Prepositional Phrase Attachment Corpus.
The PP Attachment Corpus contains several files having the format:
sentence_id verb noun1 preposition noun2 attachment
For example:
42960 gives authority to administration V
46742 gives inventors of microchip N
The PP attachment is to the verb phrase (V) or noun phrase (N), i.e.:
(VP gives (NP authority) (PP to administration))
(VP gives (NP inventors (PP of microchip)))
The corpus contains the following files:
training: training set
devset: development test set, used for algorithm development.
test: test set, used to report results
bitstrings: word classes derived from Mutual Information Clustering for the Wall Street Journal.
Ratnaparkhi, Adwait (1994). A Maximum Entropy Model for Prepositional
Phrase Attachment. Proceedings of the ARPA Human Language Technology
Conference. [http://www.cis.upenn.edu/~adwait/papers/hlt94.ps]
The PP Attachment Corpus is distributed with NLTK with the permission
of the author.
"""
from nltk.corpus.reader.api import *
from nltk.corpus.reader.util import *
class PPAttachment:
def __init__(self, sent, verb, noun1, prep, noun2, attachment):
self.sent = sent
self.verb = verb
self.noun1 = noun1
self.prep = prep
self.noun2 = noun2
self.attachment = attachment
def __repr__(self):
return (
"PPAttachment(sent=%r, verb=%r, noun1=%r, prep=%r, "
"noun2=%r, attachment=%r)"
% (self.sent, self.verb, self.noun1, self.prep, self.noun2, self.attachment)
)
class PPAttachmentCorpusReader(CorpusReader):
"""
sentence_id verb noun1 preposition noun2 attachment
"""
def attachments(self, fileids):
return concat(
[
StreamBackedCorpusView(fileid, self._read_obj_block, encoding=enc)
for (fileid, enc) in self.abspaths(fileids, True)
]
)
def tuples(self, fileids):
return concat(
[
StreamBackedCorpusView(fileid, self._read_tuple_block, encoding=enc)
for (fileid, enc) in self.abspaths(fileids, True)
]
)
def _read_tuple_block(self, stream):
line = stream.readline()
if line:
return [tuple(line.split())]
else:
return []
def _read_obj_block(self, stream):
line = stream.readline()
if line:
return [PPAttachment(*line.split())]
else:
return []
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