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Python

# Natural Language Toolkit: IEER Corpus Reader
#
# Copyright (C) 2001-2020 NLTK Project
# Author: Steven Bird <stevenbird1@gmail.com>
# Edward Loper <edloper@gmail.com>
# URL: <http://nltk.org/>
# For license information, see LICENSE.TXT
"""
Corpus reader for the Information Extraction and Entity Recognition Corpus.
NIST 1999 Information Extraction: Entity Recognition Evaluation
http://www.itl.nist.gov/iad/894.01/tests/ie-er/er_99/er_99.htm
This corpus contains the NEWSWIRE development test data for the
NIST 1999 IE-ER Evaluation. The files were taken from the
subdirectory: /ie_er_99/english/devtest/newswire/*.ref.nwt
and filenames were shortened.
The corpus contains the following files: APW_19980314, APW_19980424,
APW_19980429, NYT_19980315, NYT_19980403, and NYT_19980407.
"""
import nltk
from nltk.corpus.reader.api import *
#: A dictionary whose keys are the names of documents in this corpus;
#: and whose values are descriptions of those documents' contents.
titles = {
"APW_19980314": "Associated Press Weekly, 14 March 1998",
"APW_19980424": "Associated Press Weekly, 24 April 1998",
"APW_19980429": "Associated Press Weekly, 29 April 1998",
"NYT_19980315": "New York Times, 15 March 1998",
"NYT_19980403": "New York Times, 3 April 1998",
"NYT_19980407": "New York Times, 7 April 1998",
}
#: A list of all documents in this corpus.
documents = sorted(titles)
class IEERDocument(object):
def __init__(self, text, docno=None, doctype=None, date_time=None, headline=""):
self.text = text
self.docno = docno
self.doctype = doctype
self.date_time = date_time
self.headline = headline
def __repr__(self):
if self.headline:
headline = " ".join(self.headline.leaves())
else:
headline = (
" ".join([w for w in self.text.leaves() if w[:1] != "<"][:12]) + "..."
)
if self.docno is not None:
return "<IEERDocument %s: %r>" % (self.docno, headline)
else:
return "<IEERDocument: %r>" % headline
class IEERCorpusReader(CorpusReader):
"""
"""
def raw(self, fileids=None):
if fileids is None:
fileids = self._fileids
elif isinstance(fileids, str):
fileids = [fileids]
return concat([self.open(f).read() for f in fileids])
def docs(self, fileids=None):
return concat(
[
StreamBackedCorpusView(fileid, self._read_block, encoding=enc)
for (fileid, enc) in self.abspaths(fileids, True)
]
)
def parsed_docs(self, fileids=None):
return concat(
[
StreamBackedCorpusView(fileid, self._read_parsed_block, encoding=enc)
for (fileid, enc) in self.abspaths(fileids, True)
]
)
def _read_parsed_block(self, stream):
# TODO: figure out while empty documents are being returned
return [
self._parse(doc)
for doc in self._read_block(stream)
if self._parse(doc).docno is not None
]
def _parse(self, doc):
val = nltk.chunk.ieerstr2tree(doc, root_label="DOCUMENT")
if isinstance(val, dict):
return IEERDocument(**val)
else:
return IEERDocument(val)
def _read_block(self, stream):
out = []
# Skip any preamble.
while True:
line = stream.readline()
if not line:
break
if line.strip() == "<DOC>":
break
out.append(line)
# Read the document
while True:
line = stream.readline()
if not line:
break
out.append(line)
if line.strip() == "</DOC>":
break
# Return the document
return ["\n".join(out)]