Datasets:
Languages:
Russian
Multilinguality:
monolingual
Size Categories:
unknown
Language Creators:
machine-generated
Annotations Creators:
expert-generated
Source Datasets:
original
ArXiv:
License:
"""HSE Russian dataset by Glushkova et al..""" | |
import datasets | |
import pandas as pd | |
from functools import reduce | |
_CITATION = """ | |
@article{glushkova2019char, | |
title={Char-RNN and Active Learning for Hashtag Segmentation}, | |
author={Glushkova, Taisiya and Artemova, Ekaterina}, | |
journal={arXiv preprint arXiv:1911.03270}, | |
year={2019} | |
} | |
""" | |
_DESCRIPTION = """ | |
2000 real hashtags collected from several pages about civil services on vk.com (a Russian social network) | |
and then segmented manually. | |
""" | |
_URL = "https://raw.githubusercontent.com/glushkovato/hashtag_segmentation/master/data/test_rus.csv" | |
class HSE(datasets.GeneratorBasedBuilder): | |
VERSION = datasets.Version("1.0.0") | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{ | |
"index": datasets.Value("int32"), | |
"hashtag": datasets.Value("string"), | |
"segmentation": datasets.Value("string") | |
} | |
), | |
supervised_keys=None, | |
homepage="https://github.com/glushkovato/hashtag_segmentation", | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
downloaded_files = dl_manager.download(_URL) | |
return [ | |
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files }), | |
] | |
def _generate_examples(self, filepath): | |
df = pd.read_csv(filepath) | |
records = df.to_dict("records") | |
def get_segmentation(a, b): | |
return "".join(reduce(lambda x,y: x + y, list(zip(a,b)))).replace("0","").replace("1"," ").strip() | |
for idx, row in enumerate(records): | |
yield idx, { | |
"index": idx, | |
"hashtag": row["hashtag"], | |
"segmentation": get_segmentation( | |
row["hashtag"], | |
row["true_segmentation"] | |
)} |