Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
part-of-speech
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 | |
| """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 | |