# 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