twitter_pos_vcb.py

# 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
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# 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