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| """Stance prediction for Russian: data and analysis""" |
|
|
| import csv |
| import os |
|
|
| import datasets |
|
|
|
|
| logger = datasets.logging.get_logger(__name__) |
|
|
|
|
| _CITATION = """\ |
| @inproceedings{lozhnikov2018stance, |
| title={Stance prediction for Russian: data and analysis}, |
| author={Lozhnikov, Nikita and Derczynski, Leon and Mazzara, Manuel}, |
| booktitle={International Conference in Software Engineering for Defence Applications}, |
| pages={176--186}, |
| year={2018}, |
| organization={Springer} |
| } |
| """ |
|
|
| _DESCRIPTION = """\ |
| This is a stance prediction dataset in Russian. The dataset contains comments on news articles, |
| and rows are a comment, the title of the news article it responds to, and the stance of the comment |
| towards the article. |
| """ |
|
|
| _URL = "rustance_dataset.csv" |
|
|
|
|
| class RuStanceConfig(datasets.BuilderConfig): |
| """BuilderConfig for RuStance""" |
|
|
| def __init__(self, **kwargs): |
| """BuilderConfig RuStance. |
| |
| Args: |
| **kwargs: keyword arguments forwarded to super. |
| """ |
| super(RuStanceConfig, self).__init__(**kwargs) |
|
|
|
|
| class RuStance(datasets.GeneratorBasedBuilder): |
| """RuStance dataset.""" |
|
|
| BUILDER_CONFIGS = [ |
| RuStanceConfig(name="rustance", version=datasets.Version("1.0.0"), description="Stance dataset in Russian"), |
| ] |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features( |
| { |
| "id": datasets.Value("string"), |
| "text": datasets.Value("string"), |
| "title": datasets.Value("string"), |
| "stance": datasets.features.ClassLabel( |
| names=[ |
| "support", |
| "deny", |
| "query", |
| "comment", |
| ] |
| ) |
| } |
| ), |
| supervised_keys=None, |
| homepage="https://link.springer.com/chapter/10.1007/978-3-030-14687-0_16", |
| citation=_CITATION, |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| """Returns SplitGenerators.""" |
| downloaded_file = dl_manager.download_and_extract(_URL) |
|
|
| return [ |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file}), |
| ] |
|
|
| def _generate_examples(self, filepath): |
| logger.info("⏳ Generating examples from = %s", filepath) |
| with open(filepath, encoding="utf-8") as f: |
| rustance_reader = csv.DictReader(f, delimiter=";", quotechar='"') |
| guid = 0 |
| for instance in rustance_reader: |
| instance["id"] = str(guid) |
| if instance['Stance'] == "s": |
| instance['Stance'] = "support" |
| elif instance['Stance'] == "d": |
| instance['Stance'] = "deny" |
| elif instance['Stance'] == "q": |
| instance['Stance'] = "query" |
| elif instance['Stance'] == "c": |
| instance['Stance'] = "comment" |
|
|
| instance["text"] = instance.pop("Text") |
| instance["title"] = instance.pop("Title") |
| instance["stance"] = instance.pop("Stance") |
|
|
| yield guid, instance |
| guid += 1 |
|
|
