ner-wikinews-dataset.py

import json
from typing import Generator

import datasets

_CITATION = ""
_DESCRIPTION = "This is a dataset of Wikinews articles manually labeled with the named entity label."
_HOMEPAGE = "https://ja.wikinews.org/wiki/%E3%83%A1%E3%82%A4%E3%83%B3%E3%83%9A%E3%83%BC%E3%82%B8"
_LICENSE = "This work is licensed under CC BY 2.5"
_URL = "https://huggingface.co/datasets/llm-book/ner-wikinews-dataset/raw/main/annotated_wikinews.json"


class NerWikinewsDataset(datasets.GeneratorBasedBuilder):
    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "curid": datasets.Value("string"),
                    "text": datasets.Value("string"),
                    "entities": [
                        {
                            "name": datasets.Value("string"),
                            "span": datasets.Sequence(
                                datasets.Value("int64"), length=2
                            ),
                            "type": datasets.Value("string"),
                        }
                    ],
                }
            ),
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _convert_data_format(
        self, annotated_data: list[dict[str, any]]
    ) -> list[dict[str, any]]:
        outputs = []
        for data in annotated_data:
            if data["annotations"] == []:
                continue
            entities = []
            for annotations in data["annotations"]:
                for result in annotations["result"]:
                    entities.append(
                        {
                            "name": result["value"]["text"],
                            "span": [
                                result["value"]["start"],
                                result["value"]["end"],
                            ],
                            "type": result["value"]["labels"][0],
                        }
                    )
            if entities != []:
                entities = sorted(entities, key=lambda x: x["span"][0])
            outputs.append(
                {
                    "curid": data["id"],
                    "text": data["data"]["text"],
                    "entities": entities,
                }
            )
        return outputs

    def _split_generators(
        self, dl_manager: datasets.DownloadManager
    ) -> list[datasets.SplitGenerator]:
        data_file = dl_manager.download_and_extract(_URL)
        with open(data_file, "r", encoding="utf-8") as f:
            data = json.load(f)
        data = self._convert_data_format(data)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={"data": data},
            ),
        ]

    def _generate_examples(self, data: list[dict[str, str]]) -> Generator:
        for key, d in enumerate(data):
            yield key, {
                "curid": d["curid"],
                "text": d["text"],
                "entities": d["entities"],
            }