naamapadam.py

import json
import os

import datasets

_CITATION = """\

"""

_DESCRIPTION = """\

"""
_HOMEPAGE = "https://indicnlp.ai4bharat.org/"

_LICENSE = "Creative Commons Attribution-NonCommercial 4.0 International Public License"

_URL = "https://huggingface.co/datasets/ai4bharat/naamapadam/resolve/main/data/{}_IndicNER_v{}.zip"

_LANGUAGES = ["as", "bn", "gu", "hi", "kn", "ml", "mr", "or", "pa", "ta", "te"]


class NaamapadamPR(datasets.GeneratorBasedBuilder):
    VERSION = datasets.Version("1.0.0")

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            name="{}".format(lang), version=datasets.Version("1.0.0")
        )
        for lang in _LANGUAGES
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "tokens": datasets.Sequence(datasets.Value("string")),
                    "ner_tags": datasets.Sequence(
                        datasets.features.ClassLabel(
                            names=[
                                "O",
                                "B-PER",
                                "I-PER",
                                "B-ORG",
                                "I-ORG",
                                "B-LOC",
                                "I-LOC",
                            ]
                        )
                    ),
                }
            ),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            citation=_CITATION,
            license=_LICENSE,
            version=self.VERSION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        lang = str(self.config.name)
        url = _URL.format(lang, self.VERSION.version_str[:-2])

        data_dir = dl_manager.download_and_extract(url)

        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "filepath": os.path.join(data_dir, lang + "_train.json"),
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "filepath": os.path.join(data_dir, lang + "_test.json"),
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                gen_kwargs={
                    "filepath": os.path.join(data_dir, lang + "_val.json"),
                },
            ),
        ]

    def _generate_examples(self, filepath):
        """Yields examples as (key, example) tuples."""
        with open(filepath, encoding="utf-8") as f:
            for idx_, row in enumerate(f):
                data = json.loads(row)
                yield idx_, {"tokens": data["words"], "ner_tags": data["ner"]}