ANTILLES.py

# coding=utf-8
# Source: https://github.com/huggingface/datasets/blob/master/templates/new_dataset_script.py

"""ANTILLES Corpus"""

import os
import datasets
from tqdm import tqdm

logger = datasets.logging.get_logger(__name__)

_CITATION = """
@misc{
    universaldependencies,
    title={UniversalDependencies/UD_French-GSD},
    url={https://github.com/UniversalDependencies/UD_French-GSD}, journal={GitHub},
    author={UniversalDependencies}
}

@inproceedings{mcdonald-etal-2013-universal,
    title = {{U}niversal {D}ependency Annotation for Multilingual Parsing},
    author = {
        McDonald, Ryan  and
        Nivre, Joakim  and
        Quirmbach-Brundage, Yvonne  and
        Goldberg, Yoav  and
        Das, Dipanjan  and
        Ganchev, Kuzman  and
        Hall, Keith  and
        Petrov, Slav  and
        Zhang, Hao  and
        Tackstrom, Oscar  and
        Bedini, Claudia  and
        Bertomeu Castello, Nuria  and
        Lee, Jungmee
    },
    booktitle = {Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
    month = aug,
    year = {2013},
    address = {Sofia, Bulgaria},
    publisher = {Association for Computational Linguistics},
    url = {https://aclanthology.org/P13-2017},
    pages = {92--97",
}

@techreport{
    LIA_TAGG,
    author = {Frédéric Béchet},
    title = {LIA_TAGG: a statistical POS tagger + syntactic bracketer},
    institution = {Aix-Marseille University & CNRS},
    year = {2001}
}
"""

_LICENSE = """
For the following languages

  German, Spanish, French, Indonesian, Italian, Japanese, Korean and Brazilian
  Portuguese

we will distinguish between two portions of the data.

1. The underlying text for sentences that were annotated. This data Google
   asserts no ownership over and no copyright over. Some or all of these
   sentences may be copyrighted in some jurisdictions.  Where copyrighted,
   Google collected these sentences under exceptions to copyright or implied
   license rights.  GOOGLE MAKES THEM AVAILABLE TO YOU 'AS IS', WITHOUT ANY
   WARRANTY OF ANY KIND, WHETHER EXPRESS OR IMPLIED.

2. The annotations -- part-of-speech tags and dependency annotations. These are
   made available under a CC BY-SA 4.0. GOOGLE MAKES
   THEM AVAILABLE TO YOU 'AS IS', WITHOUT ANY WARRANTY OF ANY KIND, WHETHER
   EXPRESS OR IMPLIED. See attached LICENSE file for the text of CC BY-NC-SA.

Portions of the German data were sampled from the CoNLL 2006 Tiger Treebank
data. Hans Uszkoreit graciously gave permission to use the underlying
sentences in this data as part of this release.

Any use of the data should reference the above plus:

  Universal Dependency Annotation for Multilingual Parsing
  Ryan McDonald, Joakim Nivre, Yvonne Quirmbach-Brundage, Yoav Goldberg,
  Dipanjan Das, Kuzman Ganchev, Keith Hall, Slav Petrov, Hao Zhang,
  Oscar Tackstrom, Claudia Bedini, Nuria Bertomeu Castello and Jungmee Lee
  Proceedings of ACL 2013
"""

_DESCRIPTION = "No description"

_URLS = {
    "ANTILLES": "https://huggingface.co/datasets/qanastek/ANTILLES/resolve/main/ANTILLES.zip"
}

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

    VERSION = datasets.Version("1.1.0")

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name="ANTILLES", version=VERSION, description="The ANTILLES corpora"),
    ]

    DEFAULT_CONFIG_NAME = "ANTILLES"

    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 = ['PART', 'PDEMMP', 'PREFS', 'PINDMP', 'DINTMS', 'NUM', 'PINTFS', 'NFP', 'PUNCT', 'PRELMS', 'NOUN', 'PPER3MS', 'AUX', 'COSUB', 'ADJ', 'VPPRE', 'COCO', 'ADJMP', 'X', 'NMS', 'PINDMS', 'DETFS', 'PPER2S', 'PREFP', 'PPER3MP', 'PRELMP', 'PINDFS', 'PRON', 'PREP', 'PPOBJMP', 'ADJFS', 'DET', 'ADJFP', 'PDEMFP', 'PREL', 'PPER3FS', 'VPPFS', 'PPER3FP', 'CHIF', 'NMP', 'SYM', 'NFS', 'VERB', 'PREF', 'VPPFP', 'PDEMMS', 'XFAMIL', 'PINDFP', 'VPPMP', 'YPFOR', 'ADV', 'PRELFS', 'DINTFS', 'DETMS', 'PPOBJFP', 'PPOBJMS', 'VPPMS', 'INTJ', 'PROPN', 'PDEMFS', 'PPER1S', 'PRELFP', 'MOTINC', 'ADJMS', 'PPOBJFS']
                        )
                    ),
                }
            ),
            supervised_keys=None,
            homepage="https://github.com/qanastek/ANTILLES",
            citation=_CITATION,
            license=_LICENSE,
        )

    def _split_generators(self, dl_manager):

        urls = _URLS[self.config.name]
        data_dir = dl_manager.download_and_extract(urls)

        TRAIN_PATH = 'train.conllu'
        DEV_PATH   = 'dev.conllu'
        TEST_PATH  = 'test.conllu'

        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "filepath": os.path.join(data_dir, TRAIN_PATH),
                    "split": "train",
                }
            ),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                gen_kwargs={
                    "filepath": os.path.join(data_dir, DEV_PATH),
                    "split": "dev",
                }
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "filepath": os.path.join(data_dir, TEST_PATH),
                    "split": "test",
                }
            ),
        ]
        

    def _generate_examples(self, filepath, split):

        logger.info("⏳ Generating examples from = %s", filepath)

        with open(filepath, encoding="utf-8") as f:

            guid = 0
            tokens = []
            pos_tags = []

            for line in tqdm(f):

                if "#" in line or line == "" or line == "\n":

                    if tokens:

                        yield guid, {
                            "id": str(guid),
                            "tokens": tokens,
                            "pos_tags": pos_tags,
                        }

                        guid += 1
                        tokens = []
                        pos_tags = []

                else:

                    splits = line.split('\t')
                    tokens.append(splits[1])

                    pos_tags.append(splits[3].rstrip() if "_" not in splits[3] else "X")

            yield guid, {
                "id": str(guid),
                "tokens": tokens,
                "pos_tags": pos_tags,
            }