File size: 4,775 Bytes
877a3f4 |
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 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 |
# Author: Roman Janík
# Script for local loading PONER 1.0 CoNNL dataset and converting it to Hugging Face dataset format.
#
# This script if a modified version of conll2003/conll2003.py script by HuggingFace Datasets Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import datasets
logger = datasets.logging.get_logger(__name__)
_CITATION = """
-
"""
_DESCRIPTION = """\
This is a Pero OCR NER 1.0 dataset in the CoNLL format. Each line in
the corpus contains information about one word/token. The first column is the actual
word, the second column is a Named Entity class in a BIO format. An empty line is a sentence separator.
"""
_TRAINING_FILE = "poner_train.conll"
_DEV_FILE = "poner_dev.conll"
_TEST_FILE = "poner_test.conll"
class Poner1_0ConllConfig(datasets.BuilderConfig):
"""BuilderConfig for PONER 1.0 CoNNL"""
def __init__(self, **kwargs):
"""BuilderConfig for PONER 1.0 CoNNL.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(Poner1_0ConllConfig, self).__init__(**kwargs)
class Poner1_0Conll(datasets.GeneratorBasedBuilder):
"""PONER 1.0 CoNNL dataset."""
BUILDER_CONFIGS = [
Poner1_0ConllConfig(name="poner1_0conll", version=datasets.Version("1.0.0"),
description="PONER 1.0 CoNNL dataset"),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"id": datasets.Value("string"),
"tokens": datasets.Sequence(datasets.Value("string")),
"ner_tags": datasets.Sequence(
datasets.features.ClassLabel(
names=[
"O",
"B-p",
"I-p",
"B-i",
"I-i",
"B-g",
"I-g",
"B-t",
"I-t",
"B-o",
"I-o"
]
)
),
}
),
supervised_keys=None,
homepage="https://pero-ocr.fit.vutbr.cz",
citation=_CITATION,
)
def _split_generators(self, dl_manager, dataset_path="../../../datasets/poner1.0"):
"""Returns SplitGenerators."""
data_files = {
"train": os.path.join(dataset_path, _TRAINING_FILE),
"dev": os.path.join(dataset_path, _DEV_FILE),
"test": os.path.join(dataset_path, _TEST_FILE),
}
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_files["train"]}),
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": data_files["dev"]}),
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_files["test"]}),
]
def _generate_examples(self, filepath):
logger.info("⏳ Generating examples from = %s", filepath)
with open(filepath, encoding="utf-8") as f:
guid = 0
tokens = []
ner_tags = []
for line in f:
if line.startswith("-DOCSTART-") or line == "" or line == "\n":
if tokens:
yield guid, {
"id": str(guid),
"tokens": tokens,
"ner_tags": ner_tags,
}
guid += 1
tokens = []
ner_tags = []
else:
# conll2003 tokens are space separated
splits = line.split(" ")
tokens.append(splits[0])
ner_tags.append(splits[1].rstrip())
# last example
if tokens:
yield guid, {
"id": str(guid),
"tokens": tokens,
"ner_tags": ner_tags,
}
|