def __init__(self, filename):
initialize(self, locals())
self.reader = iter(possibly_compressed_file(filename))
self.header = parse_kv_list(self.reader.next())
assert 'S' in self.header
self.num_sentences = self.header['S']
def __init__(self, filename):
initialize(self, locals())
self.reader = iter(possibly_compressed_file(filename))
self.header = parse_kv_list(next(self.reader))
assert 'S' in self.header
self.num_sentences = self.header['S']
def __init__(self, corpus_filename1, corpus_filename2, mapping1, mapping2,
merged_corpus_filename, merged_mapping_filename,
verbose=True, warn_only=False):
initialize(self, locals())
self.read_mappings()
self.make_merged_mapping()
self.make_merged_feature_values()
def __init__(self, file_id, id, event_type, event_term, args):
if file_id is not None:
file_id = file_id.basename()
try:
file_id = int(file_id)
except ValueError:
pass
initialize(self, locals())
self._not_in_repr = ['file_id', 'id']
def __init__(self, file_id, id, event_type, event_term, args):
if file_id is not None:
file_id = file_id.basename()
try:
file_id = int(file_id)
except ValueError:
pass
initialize(self, locals())
self._not_in_repr = ['file_id', 'id']
def __init__(self, file_id, *terms):
if file_id is not None:
file_id = file_id.basename()
try:
file_id = int(file_id)
except ValueError:
pass
# this is so we have some unique ID
id = (file_id, terms)
initialize(self, locals())
self._not_in_repr = ['file_id', 'id']
def __init__(self, file_id, *terms):
if file_id is not None:
file_id = file_id.basename()
try:
file_id = int(file_id)
except ValueError:
pass
# this is so we have some unique ID
id = (file_id, terms)
initialize(self, locals())
self._not_in_repr = ['file_id', 'id']
def __init__(self, file_id, id, term_type, start_offset, end_offset, name, given):
start_offset = int(start_offset)
end_offset = int(end_offset)
if file_id is not None:
file_id = file_id.basename()
try:
file_id = int(file_id)
except ValueError:
pass
initialize(self, locals())
self._not_in_repr = ['file_id', 'id']
self._already_expanded = False
def __init__(self, file_id, id, term_type, start_offset, end_offset, name,
given):
start_offset = int(start_offset)
end_offset = int(end_offset)
if file_id is not None:
file_id = file_id.basename()
try:
file_id = int(file_id)
except ValueError:
pass
initialize(self, locals())
self._not_in_repr = ['file_id', 'id']
self._already_expanded = False
def __init__(self,
corpus_filename1,
corpus_filename2,
mapping1,
mapping2,
merged_corpus_filename,
merged_mapping_filename,
verbose=True,
warn_only=False):
initialize(self, locals())
self.read_mappings()
self.make_merged_mapping()
self.make_merged_feature_values()
def __init__(self, gold_brackets, parses, index):
initialize(self, locals())
def __init__(self, proposed_brackets, matched_brackets, features):
features = defaultdict(int, features)
initialize(self, locals())
def __init__(self, proposed_brackets, matched_brackets, features):
initialize(self, locals())
def __init__(self, gold_brackets, parses, index):
initialize(self, locals())
def __init__(self, proposed_brackets, matched_brackets, features):
features = defaultdict(int, features)
initialize(self, locals())
def __init__(self, proposed_brackets, matched_brackets, features):
initialize(self, locals())