from pathlib import Path
from deeppavlov.core.common.registry import register
from deeppavlov.core.data.dataset_reader import DatasetReader
from deeppavlov.core.data.utils import download_decompress
[docs]@register('conll2003_reader')
class Conll2003DatasetReader(DatasetReader):
"""Class to read training datasets in CoNLL-2003 format"""
def read(self,
data_path: str,
dataset_name: str = None,
provide_pos: bool = False,
provide_doc_ids: bool = False):
self.provide_pos = provide_pos
self.provide_doc_ids = provide_doc_ids
self.num_docs = 0
self.x_is_tuple = self.provide_pos or self.provide_doc_ids
data_path = Path(data_path)
files = list(data_path.glob('*.txt'))
if 'train.txt' not in {file_path.name for file_path in files}:
if dataset_name == 'conll2003':
url = 'http://files.deeppavlov.ai/deeppavlov_data/conll2003_v2.tar.gz'
elif dataset_name == 'collection_rus':
url = 'http://files.deeppavlov.ai/deeppavlov_data/collection3_v2.tar.gz'
elif dataset_name == 'ontonotes':
url = 'http://files.deeppavlov.ai/deeppavlov_data/ontonotes_ner.tar.gz'
else:
raise RuntimeError('train.txt not found in "{}"'.format(data_path))
data_path.mkdir(exist_ok=True, parents=True)
download_decompress(url, data_path)
files = list(data_path.glob('*.txt'))
dataset = {}
for file_name in files:
name = file_name.with_suffix('').name
dataset[name] = self.parse_ner_file(file_name)
return dataset
def parse_ner_file(self, file_name: Path):
samples = []
with file_name.open(encoding='utf8') as f:
tokens = []
pos_tags = []
tags = []
for line in f:
# Check end of the document
if 'DOCSTART' in line:
if len(tokens) > 1:
x = tokens if not self.x_is_tuple else (tokens,)
if self.provide_pos:
x = x + (pos_tags,)
if self.provide_doc_ids:
x = x + (self.num_docs,)
samples.append((x, tags))
tokens = []
pos_tags = []
tags = []
self.num_docs += 1
elif len(line) < 2:
if len(tokens) > 0:
x = tokens if not self.x_is_tuple else (tokens,)
if self.provide_pos:
x = x + (pos_tags,)
if self.provide_doc_ids:
x = x + (self.num_docs,)
samples.append((x, tags))
tokens = []
pos_tags = []
tags = []
else:
if self.provide_pos:
token, pos, *_, tag = line.split()
pos_tags.append(pos)
else:
token, *_, tag = line.split()
tags.append(tag)
tokens.append(token)
if tokens:
x = tokens if not self.x_is_tuple else (tokens,)
if self.provide_pos:
x = x + (pos_tags,)
if self.provide_doc_ids:
x = x + (self.num_docs,)
samples.append((x, tags))
self.num_docs += 1
return samples