Datasets:

strombergnlp
/

twitter_pos_vcb

	# 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
	"""Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition"""

	import os

	import datasets


	logger = datasets.logging.get_logger(__name__)


	_CITATION = """\
	@inproceedings{derczynski2013twitter,
	title={Twitter part-of-speech tagging for all: Overcoming sparse and noisy data},
	author={Derczynski, Leon and Ritter, Alan and Clark, Sam and Bontcheva, Kalina},
	booktitle={Proceedings of the international conference recent advances in natural language processing ranlp 2013},
	pages={198--206},
	year={2013}
	}
	"""

	_DESCRIPTION = """\
	Part-of-speech information is basic NLP task. However, Twitter text
	is difficult to part-of-speech tag: it is noisy, with linguistic errors and idiosyncratic style.
	This data is the vote-constrained bootstrapped data generate to support state-of-the-art results.

	The data is about 1.5 million English tweets annotated for part-of-speech using Ritter's extension of the PTB tagset.
	The tweets are from 2012 and 2013, tokenized using the GATE tokenizer and tagged
	jointly using the CMU ARK tagger and Ritter's T-POS tagger. Only when both these taggers' outputs
	are completely compatible over a whole tweet, is that tweet added to the dataset.

	This data is recommend for use a training data only, and not evaluation data.

	For more details see https://gate.ac.uk/wiki/twitter-postagger.html and https://aclanthology.org/R13-1026.pdf
	"""

	_URL = "http://downloads.gate.ac.uk/twitter/twitter_bootstrap_corpus.tar.gz"
	_TRAINING_FILE = "gate_twitter_bootstrap_corpus.1543K.tokens"


	class TwitterPosVcbConfig(datasets.BuilderConfig):
	"""BuilderConfig for TwitterPosVcb"""

	def __init__(self, **kwargs):
	"""BuilderConfig forConll2003.

	Args:
	**kwargs: keyword arguments forwarded to super.
	"""
	super(TwitterPosVcbConfig, self).__init__(**kwargs)


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

	BUILDER_CONFIGS = [
	TwitterPosVcbConfig(name="twitter-pos-vcb", version=datasets.Version("1.0.0"), description="English Twitter PoS bootstrap 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",
	"RT",
	"HT",
	"USR",
	"URL",
	]
	)
	),
	}
	),
	supervised_keys=None,
	homepage="https://gate.ac.uk/wiki/twitter-postagger.html",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	downloaded_file = dl_manager.download_and_extract(_URL)
	data_files = {
	"train": os.path.join(downloaded_file, _TRAINING_FILE),
	}

	return [
	datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_files["train"]}),
	]

	def _generate_examples(self, filepath):
	logger.info("⏳ Generating examples from = %s", filepath)
	with open(filepath, encoding="utf-8") as f:
	guid = 0
	for line in f:
	tokens = []
	pos_tags = []
	if line.startswith("-DOCSTART-") or line.strip() == "" or line == "\n":
	continue
	else:
	# twitter-pos-vcb gives one seq per line, as token_tag
	annotated_words = line.strip().split(' ')
	tokens = ['_'.join(token.split('_')[:-1]) for token in annotated_words]
	pos_tags = [token.split('_')[-1] for token in annotated_words]
	yield guid, {
	"id": str(guid),
	"tokens": tokens,
	"pos_tags": pos_tags,
	}
	guid += 1