Datasets:
conllpp

	# 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
	"""CrossWeigh: Training Named Entity Tagger from Imperfect Annotations"""

	import logging

	import datasets


	_CITATION = """\
	@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 = """\
	CoNLLpp is a corrected version of the CoNLL2003 NER dataset where labels of 5.38% of the sentences in the test set
	have been manually corrected. The training set and development set are included for completeness.
	For more details see https://www.aclweb.org/anthology/D19-1519/ and https://github.com/ZihanWangKi/CrossWeigh
	"""

	_URL = "https://github.com/ZihanWangKi/CrossWeigh/raw/master/data/"
	_TRAINING_FILE = "conllpp_train.txt"
	_DEV_FILE = "conllpp_dev.txt"
	_TEST_FILE = "conllpp_test.txt"


	class ConllppConfig(datasets.BuilderConfig):
	"""BuilderConfig for Conll2003"""

	def __init__(self, **kwargs):
	"""BuilderConfig forConll2003.
	Args:
	**kwargs: keyword arguments forwarded to super.
	"""
	super(ConllppConfig, self).__init__(**kwargs)


	class Conllpp(datasets.GeneratorBasedBuilder):
	"""Conllpp dataset."""

	BUILDER_CONFIGS = [
	ConllppConfig(name="conllpp", version=datasets.Version("1.0.0"), description="Conllpp dataset"),
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"id": datasets.Value("string"),
	"tokens": datasets.Sequence(datasets.Value("string")),
	"pos_tags": datasets.Sequence(
	datasets.features.ClassLabel(
	names=[
	'"',
	"''",
	"#",
	"$",
	"(",
	")",
	",",
	".",
	":",
	"``",
	"CC",
	"CD",
	"DT",
	"EX",
	"FW",
	"IN",
	"JJ",
	"JJR",
	"JJS",
	"LS",
	"MD",
	"NN",
	"NNP",
	"NNPS",
	"NNS",
	"NN\|SYM",
	"PDT",
	"POS",
	"PRP",
	"PRP$",
	"RB",
	"RBR",
	"RBS",
	"RP",
	"SYM",
	"TO",
	"UH",
	"VB",
	"VBD",
	"VBG",
	"VBN",
	"VBP",
	"VBZ",
	"WDT",
	"WP",
	"WP$",
	"WRB",
	]
	)
	),
	"chunk_tags": datasets.Sequence(
	datasets.features.ClassLabel(
	names=[
	"O",
	"B-ADJP",
	"I-ADJP",
	"B-ADVP",
	"I-ADVP",
	"B-CONJP",
	"I-CONJP",
	"B-INTJ",
	"I-INTJ",
	"B-LST",
	"I-LST",
	"B-NP",
	"I-NP",
	"B-PP",
	"I-PP",
	"B-PRT",
	"I-PRT",
	"B-SBAR",
	"I-SBAR",
	"B-UCP",
	"I-UCP",
	"B-VP",
	"I-VP",
	]
	)
	),
	"ner_tags": datasets.Sequence(
	datasets.features.ClassLabel(
	names=[
	"O",
	"B-PER",
	"I-PER",
	"B-ORG",
	"I-ORG",
	"B-LOC",
	"I-LOC",
	"B-MISC",
	"I-MISC",
	]
	)
	),
	}
	),
	supervised_keys=None,
	homepage="https://github.com/ZihanWangKi/CrossWeigh",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	urls_to_download = {
	"train": f"{_URL}{_TRAINING_FILE}",
	"dev": f"{_URL}{_DEV_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["dev"]}),
	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 = []
	pos_tags = []
	chunk_tags = []
	ner_tags = []
	for line in f:
	if line.startswith("-DOCSTART-") or line == "" or line == "\n":
	if tokens:
	yield guid, {
	"id": str(guid),
	"tokens": tokens,
	"pos_tags": pos_tags,
	"chunk_tags": chunk_tags,
	"ner_tags": ner_tags,
	}
	guid += 1
	tokens = []
	pos_tags = []
	chunk_tags = []
	ner_tags = []
	else:
	# conll2003 tokens are space separated
	splits = line.split(" ")
	tokens.append(splits[0])
	pos_tags.append(splits[1])
	chunk_tags.append(splits[2])
	ner_tags.append(splits[3].rstrip())
	# last example
	if tokens:
	yield guid, {
	"id": str(guid),
	"tokens": tokens,
	"pos_tags": pos_tags,
	"chunk_tags": chunk_tags,
	"ner_tags": ner_tags,
	}