nordic_langid.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
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# Lint as: python3
"""NordicDSL: A language identification datasets for Nordic languages"""

import csv
import os

import datasets


logger = datasets.logging.get_logger(__name__)


_CITATION = """\
@inproceedings{haas-derczynski-2021-discriminating,
    title = "Discriminating Between Similar Nordic Languages",
    author = "Haas, Ren{\'e}  and
      Derczynski, Leon",
    booktitle = "Proceedings of the Eighth Workshop on NLP for Similar Languages, Varieties and Dialects",
    month = apr,
    year = "2021",
    address = "Kiyv, Ukraine",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.vardial-1.8",
    pages = "67--75",
}

"""

_DESCRIPTION = """\
Automatic language identification is a challenging problem. Discriminating
between closely related languages is especially difficult. This paper presents
a machine learning approach for automatic language identification for the
Nordic languages, which often suffer miscategorisation by existing 
state-of-the-art tools. Concretely we will focus on discrimination between six 
Nordic languages: Danish, Swedish, Norwegian (Nynorsk), Norwegian (Bokmål), 
Faroese and Icelandic.

This is the data for the tasks. Two variants are provided: 10K and 50K, with
holding 10,000 and 50,000 examples for each language respectively.

"""

_URLS = {
    "10K": "nordic_dsl_10000",
    "50K": "nordic_dsl_50000",
}


class NordicLangIdConfig(datasets.BuilderConfig):
    """BuilderConfig for NordicLangId"""

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

        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(NordicLangIdConfig, self).__init__(**kwargs)


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

    VERSION = datasets.Version("1.0.0")

    BUILDER_CONFIGS = [
        NordicLangIdConfig(
            name="10k", 
            description="Data for distinguishing between similar Nordic languages: 10k examples per class",
            version=VERSION, 
        ),
        NordicLangIdConfig(
            name="50k", 
            description="Data for distinguishing between similar Nordic languages: 50k examples per class",
            version=VERSION, 
        ),
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "id": datasets.Value("string"),
                    "sentence": datasets.Value("string"),
                    "language": datasets.features.ClassLabel(
                        names=[
                            "dk",
                            "sv",
                            "nb",
                            "nn",
                            "fo",
                            "is",
                        ]
                    ),
                }
            ),
            supervised_keys=None,
            homepage="https://aclanthology.org/2021.vardial-1.8/",
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        if self.config.name == "10k":
            downloaded_train = dl_manager.download(_URLS["10K"] + 'train.csv')
            downloaded_test = dl_manager.download(_URLS["10K"] + 'test.csv')
        elif self.config.name == "50k":
            downloaded_train = dl_manager.download(_URLS["50K"] + 'train.csv')
            downloaded_test = dl_manager.download(_URLS["50K"] + 'test.csv')

        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_train}),
            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_test}),
        ]

    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:
                line = line.strip()
                if not line:
                    continue
                if self.config.name == "10k":
                    line = line.replace('dataset10000, ', '')
                if self.config.name == "50k":
                    line = line.replace('dataset50000, ', '')
                
                instance = {
                    "id": str(guid),
                    "language": line[-2:],
                    "sentence": line[:-3],
                }

                yield guid, instance
                guid += 1