Datasets:
Tasks:
Text Classification
Sub-tasks:
natural-language-inference
Languages:
Japanese
Size:
10K - 100K
License:
File size: 2,346 Bytes
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import pandas as pd
import datasets as ds
_CITATION = """\
@InProceedings{yanaka-EtAl:2021:blackbox,
author = {Yanaka, Hitomi and Mineshima, Koji},
title = {Assessing the Generalization Capacity of Pre-trained Language Models through Japanese Adversarial Natural Language Inference},
booktitle = {Proceedings of the 2021 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP (BlackboxNLP2021)},
year = {2021},
}
"""
_DESCRIPTION = """\
"""
_HOMEPAGE = "https://github.com/verypluming/JaNLI"
_LICENSE = "CC BY-SA 4.0"
_DOWNLOAD_URL = "https://raw.githubusercontent.com/verypluming/JaNLI/main/janli.tsv"
class JaNLIDataset(ds.GeneratorBasedBuilder):
VERSION = ds.Version("1.0.0")
BUILDER_CONFIGS = [
ds.BuilderConfig(
name="default",
version=VERSION,
description=_DESCRIPTION,
),
]
def _info(self) -> ds.DatasetInfo:
features = ds.Features(
{
"id": ds.Value("int64"),
"sentence_A_Ja": ds.Value("string"),
"sentence_B_Ja": ds.Value("string"),
"entailment_label_Ja": ds.ClassLabel(names=["entailment", "non-entailment"]),
"heuristics": ds.Value("string"),
"number_of_NPs": ds.Value("int32"),
"semtag": ds.Value("string"),
}
)
return ds.DatasetInfo(
description=_DESCRIPTION,
citation=_CITATION,
homepage=_HOMEPAGE,
license=_LICENSE,
features=features,
)
def _split_generators(self, dl_manager: ds.DownloadManager):
data_path = dl_manager.download_and_extract(_DOWNLOAD_URL)
df: pd.DataFrame = pd.read_table(data_path, header=0, sep="\t", index_col=0)
df["id"] = df.index
return [
ds.SplitGenerator(
name=ds.Split.TRAIN,
gen_kwargs={"df": df[df["split"] == "train"]},
),
ds.SplitGenerator(
name=ds.Split.TEST,
gen_kwargs={"df": df[df["split"] == "test"]},
),
]
def _generate_examples(self, df: pd.DataFrame):
df = df.drop("split", axis=1)
for i, row in enumerate(df.to_dict("records")):
yield i, row
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