Coverage for nltk.corpus.reader.ppattach : 41%

# Natural Language Toolkit: PP Attachment Corpus Reader 

# 

# Copyright (C) 2001-2012 NLTK Project 

# Author: Steven Bird <sb@ldc.upenn.edu> 

#         Edward Loper <edloper@gradient.cis.upenn.edu> 

# URL: <http://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. 

""" 

import codecs 

from nltk import compat 

from .util import * 

from .api 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 raw(self, fileids=None): 

        if fileids is None: fileids = self._fileids 

        elif isinstance(fileids, compat.string_types): fileids = [fileids] 

        return concat([self.open(f).read() for f in fileids]) 

    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 []