|
from ast import literal_eval |
|
import csv |
|
|
|
import datasets |
|
|
|
logger = datasets.logging.get_logger(__name__) |
|
|
|
_CITATION = """ |
|
@inproceedings{poostchi-etal-2018-bilstm, |
|
title = "{B}i{LSTM}-{CRF} for {P}ersian Named-Entity Recognition {A}rman{P}erso{NERC}orpus: the First Entity-Annotated {P}ersian Dataset", |
|
author = "Poostchi, Hanieh and |
|
Zare Borzeshi, Ehsan and |
|
Piccardi, Massimo", |
|
booktitle = "Proceedings of the Eleventh International Conference on Language Resources and Evaluation ({LREC} 2018)", |
|
month = may, |
|
year = "2018", |
|
address = "Miyazaki, Japan", |
|
publisher = "European Language Resources Association (ELRA)", |
|
url = "https://aclanthology.org/L18-1701", |
|
} |
|
""" |
|
|
|
_DESCRIPTION = """""" |
|
|
|
_DOWNLOAD_URLS = { |
|
"train": "https://huggingface.co/datasets/hezarai/arman-ner/resolve/main/arman-ner_train.csv", |
|
"test": "https://huggingface.co/datasets/hezarai/arman-ner/resolve/main/arman-ner_test.csv", |
|
} |
|
|
|
|
|
class ArmanNERConfig(datasets.BuilderConfig): |
|
def __init__(self, **kwargs): |
|
super(ArmanNERConfig, self).__init__(**kwargs) |
|
|
|
|
|
class ArmanNER(datasets.GeneratorBasedBuilder): |
|
BUILDER_CONFIGS = [ |
|
ArmanNERConfig( |
|
name="", |
|
version=datasets.Version("1.0.0"), |
|
description=_DESCRIPTION, |
|
), |
|
] |
|
|
|
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-pro", |
|
"I-pro", |
|
"B-pers", |
|
"I-pers", |
|
"B-org", |
|
"I-org", |
|
"B-loc", |
|
"I-loc", |
|
"B-fac", |
|
"I-fac", |
|
"B-event", |
|
"I-event" |
|
] |
|
) |
|
), |
|
} |
|
), |
|
homepage="https://huggingface.co/datasets/hezarai/arman-ner", |
|
citation=_CITATION, |
|
) |
|
|
|
def _split_generators(self, dl_manager): |
|
""" |
|
Return SplitGenerators. |
|
""" |
|
|
|
train_path = dl_manager.download_and_extract(_DOWNLOAD_URLS["train"]) |
|
test_path = dl_manager.download_and_extract(_DOWNLOAD_URLS["test"]) |
|
|
|
return [ |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path} |
|
), |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TEST, gen_kwargs={"filepath": test_path} |
|
), |
|
] |
|
|
|
def _generate_examples(self, filepath): |
|
logger.info("⏳ Generating examples from = %s", filepath) |
|
with open(filepath, encoding="utf-8") as csv_file: |
|
csv_reader = csv.reader( |
|
csv_file, quotechar='"', skipinitialspace=True |
|
) |
|
|
|
next(csv_reader, None) |
|
|
|
for id_, row in enumerate(csv_reader): |
|
tokens, ner_tags = row |
|
tokens = literal_eval(tokens) |
|
ner_tags = literal_eval(ner_tags) |
|
yield id_, {"tokens": tokens, "ner_tags": ner_tags} |
|
|