File size: 1,643 Bytes
aaed6d7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 |
class OieReader:
def read(self, fn, includeNominal):
''' should set oie as a class member
as a dictionary of extractions by sentence'''
raise Exception("Don't run me")
def count(self):
''' number of extractions '''
return sum([len(extractions) for _, extractions in self.oie.items()])
def split_to_corpus(self, corpus_fn, out_fn):
"""
Given a corpus file name, containing a list of sentences
print only the extractions pertaining to it to out_fn in a tab separated format:
sent, prob, pred, arg1, arg2, ...
"""
raw_sents = [line.strip() for line in open(corpus_fn)]
with open(out_fn, 'w') as fout:
for line in self.get_tabbed().split('\n'):
data = line.split('\t')
sent = data[0]
if sent in raw_sents:
fout.write(line + '\n')
def output_tabbed(self, out_fn):
"""
Write a tabbed represenation of this corpus.
"""
with open(out_fn, 'w') as fout:
fout.write(self.get_tabbed())
def get_tabbed(self):
"""
Get a tabbed format representation of this corpus (assumes that input was
already read).
"""
return "\n".join(['\t'.join(map(str,
[ex.sent,
ex.confidence,
ex.pred,
'\t'.join(ex.args)]))
for (sent, exs) in self.oie.iteritems()
for ex in exs])
|