Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
1K - 10K
License:
# coding=utf-8 | |
# Copyright 2020 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. | |
# Lint as: python3 | |
"""INSERT TITLE""" | |
import logging | |
import datasets | |
_CITATION = """\ | |
*REDO* | |
@inproceedings{wang2019crossweigh, | |
title={CrossWeigh: Training Named Entity Tagger from Imperfect Annotations}, | |
author={Wang, Zihan and Shang, Jingbo and Liu, Liyuan and Lu, Lihao and Liu, Jiacheng and Han, Jiawei}, | |
booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)}, | |
pages={5157--5166}, | |
year={2019} | |
} | |
""" | |
_DESCRIPTION = """\ | |
**REWRITE* | |
EpiSet4NER-2 is a dataset generated from 620 rare disease abstracts labeled using statistical and rule-base methods. | |
For more details see *INSERT PAPER* and https://github.com/ncats/epi4GARD/tree/master/EpiExtract4GARD#epiextract4gard | |
""" | |
_URL = "https://raw.githubusercontent.com/ncats/epi4GARD/master/epi_extract_datasets/datasets/epi_gold/" | |
_TRAINING_FILE = "train.tsv" | |
_VAL_FILE = "val.tsv" | |
_TEST_FILE = "test.tsv" | |
class EpiSetConfig(datasets.BuilderConfig): | |
"""BuilderConfig for Conll2003""" | |
def __init__(self, **kwargs): | |
"""BuilderConfig forConll2003. | |
Args: | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
super(EpiSetConfig, self).__init__(**kwargs) | |
class EpiSet(datasets.GeneratorBasedBuilder): | |
"""EpiSet4NER by GARD.""" | |
BUILDER_CONFIGS = [ | |
EpiSetConfig(name="EpiSet4NER", version=datasets.Version("4.0.0"), description="EpiSet4NER by NIH NCATS GARD"), | |
] | |
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", #(0) | |
"B-DIS", #(1) | |
"I-DIS", #(2) | |
"B-ABRV", #(3) | |
"I-ABRV", #(4) | |
"B-EPI", #(5) | |
"I-EPI", #(6) | |
"B-STAT", #(7) | |
"I-STAT", #(8) | |
"B-LOC", #(9) | |
"I-LOC", #(10) | |
"B-DATE", #(11) | |
"I-DATE", #(12) | |
"B-SEX", #(13) | |
"I-SEX", #(14) | |
"B-ETHN", #(15) | |
"I-ETHN", #(16) | |
] | |
) | |
), | |
} | |
), | |
supervised_keys=None, | |
homepage="https://github.com/ncats/epi4GARD/tree/master/EpiExtract4GARD#epiextract4gard", | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
urls_to_download = { | |
"train": f"{_URL}{_TRAINING_FILE}", | |
"val": f"{_URL}{_VAL_FILE}", | |
"test": f"{_URL}{_TEST_FILE}", | |
} | |
downloaded_files = dl_manager.download_and_extract(urls_to_download) | |
return [ | |
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), | |
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["val"]}), | |
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}), | |
] | |
def _generate_examples(self, filepath): | |
logging.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: | |
# EpiSet tokens are space separated | |
splits = line.split("\t") | |
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, | |
} |