| import datasets |
| from datasets.download.download_manager import DownloadManager |
| import pyarrow.parquet as pq |
|
|
| _DESCRIPTION = """\ |
| The MSRA NER dataset is a Chinese Named Entity Recognition dataset |
| """ |
|
|
| _CITATION = """\ |
| @inproceedings{levow-2006-third, |
| title = "The Third International {C}hinese Language Processing Bakeoff: Word Segmentation and Named Entity Recognition", |
| author = "Levow, Gina-Anne", |
| booktitle = "Proceedings of the Fifth {SIGHAN} Workshop on {C}hinese Language Processing", |
| month = jul, |
| year = "2006", |
| address = "Sydney, Australia", |
| publisher = "Association for Computational Linguistics", |
| url = "https://aclanthology.org/W06-0115", |
| pages = "108--117", |
| } |
| """ |
|
|
| _URL = "https://huggingface.co/datasets/minskiter/msra_dev/resolve/main/" |
| _URLS = { |
| "train": _URL + "data/train.parquet", |
| 'validation': _URL + "data/validation.parquet", |
| "test": _URL + "data/test.parquet", |
| } |
|
|
| class MSRANamedEntities(datasets.GeneratorBasedBuilder): |
| VERSION = datasets.Version("1.0.0") |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features( |
| { |
| "text": datasets.Sequence(datasets.Value("string")), |
| "labels": datasets.Sequence( |
| datasets.features.ClassLabel( |
| names=[ |
| 'O', |
| 'B-NS', |
| 'M-NS', |
| 'E-NS', |
| 'S-NS', |
| 'B-NT', |
| 'M-NT', |
| 'E-NT', |
| 'S-NT', |
| 'B-NR', |
| 'M-NR', |
| 'E-NR', |
| 'S-NR' |
| ] |
| ) |
| ), |
| } |
| ), |
| supervised_keys=None, |
| homepage="https://aclanthology.org/W06-0115/", |
| citation=_CITATION, |
| ) |
|
|
| def _split_generators(self, dl_manager: DownloadManager): |
| urls_to_download = _URLS |
| download_files = dl_manager.download_and_extract(urls_to_download) |
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
| gen_kwargs={"filepath": download_files["train"]}, |
| ), |
| datasets.SplitGenerator( |
| name=datasets.Split.VALIDATION, |
| gen_kwargs={"filepath": download_files["validation"]}, |
| ), |
| datasets.SplitGenerator( |
| name=datasets.Split.TEST, |
| gen_kwargs={"filepath": download_files["test"]}, |
| ), |
| ] |
|
|
| def _generate_examples(self, filepath): |
| with open(filepath,"rb") as f: |
| with pq.ParquetFile(f) as file: |
| _id = -1 |
| for i in file.iter_batches(batch_size=64): |
| rows = i.to_pylist() |
| for row in rows: |
| _id+=1 |
| yield _id, row |
|
|