Datasets:

strombergnlp
/

twitter_pos

	# 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{ritter2011named,
	title={Named entity recognition in tweets: an experimental study},
	author={Ritter, Alan and Clark, Sam and Etzioni, Oren and others},
	booktitle={Proceedings of the 2011 conference on empirical methods in natural language processing},
	pages={1524--1534},
	year={2011}
	}

	@inproceedings{foster2011hardtoparse,
	title={\# hardtoparse: POS Tagging and Parsing the Twitterverse},
	author={Foster, Jennifer and Cetinoglu, Ozlem and Wagner, Joachim and Le Roux, Joseph and Hogan, Stephen and Nivre, Joakim and Hogan, Deirdre and Van Genabith, Josef},
	booktitle={Workshops at the Twenty-Fifth AAAI Conference on Artificial Intelligence},
	year={2011}
	}

	@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 dataset contains two datasets for English PoS tagging for tweets:

	* Ritter, with train/dev/test
	* Foster, with dev/test

	Splits defined in the Derczynski paper, but the data is from Ritter and Foster.

	For more details see:

	* https://gate.ac.uk/wiki/twitter-postagger.html
	* https://aclanthology.org/D11-1141.pdf
	* https://www.aaai.org/ocs/index.php/ws/aaaiw11/paper/download/3912/4191
	"""

	_URL = "http://downloads.gate.ac.uk/twitie/twitie-tagger.zip"
	_RITTER_TRAIN = "twitie-tagger/corpora/ritter_train.stanford"
	_RITTER_DEV = "twitie-tagger/corpora/ritter_dev.stanford"
	_RITTER_TEST = "twitie-tagger/corpora/ritter_eval.stanford"
	_FOSTER_TRAIN = None
	_FOSTER_DEV = "twitie-tagger/corpora/foster_dev.stanford"
	_FOSTER_TEST = "twitie-tagger/corpora/foster_eval.stanford"


	class TwitterPosConfig(datasets.BuilderConfig):
	"""BuilderConfig for TwitterPos"""

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

	Args:
	**kwargs: keyword arguments forwarded to super.
	"""
	super(TwitterPosConfig, self).__init__(**kwargs)
	#assert variant in ('foster', 'ritter'), (f'Unrecognised variation: {variant}')


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

	BUILDER_CONFIGS = [
	TwitterPosConfig(name="foster", description="Foster English Twitter PoS bootstrap dataset"),
	TwitterPosConfig(name="ritter", description="Ritter English Twitter PoS bootstrap dataset"),
	]

	def _info(self):
	variant = self.config.name
	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)

	if self.config.name == 'ritter':
	data_files = {
	"train": os.path.join(downloaded_file, _RITTER_TRAIN),
	"dev": os.path.join(downloaded_file, _RITTER_DEV),
	"test": os.path.join(downloaded_file, _RITTER_TEST),
	}
	elif self.config.name == 'foster':
	data_files = {
	"dev": os.path.join(downloaded_file, _FOSTER_DEV),
	"test": os.path.join(downloaded_file, _FOSTER_TEST),
	}

	splits = [
	datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": data_files["dev"]}),
	datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_files["test"]}),
	]

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

	return splits

	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:
	line = line.replace('_VPB ', '_VBP ') # tag type fixes
	line = line.replace('_TD ', '_DT ') # tag type fixes
	line = line.replace('_ADVP ', '_RB ') # tag type fixes
	line = line.replace('_NONE ', '_: ') # tag type fixes
	line = line.replace(' please_VPP ', ' please_VBP ') # tag type fixes
	line = line.replace(' ".._O ', ' ".._" ') # tag type fixes
	# twitter-pos 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