|
import logging |
|
import os |
|
|
|
import datasets as ds |
|
|
|
logger = logging.getLogger(__name__) |
|
|
|
_CITATION = """\ |
|
- 吉越 卓見, 河原 大輔, 黒橋 禎夫: 機械翻訳を用いた自然言語推論データセットの多言語化, 第244回自然言語処理研究会, (2020.7.3). |
|
- Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015. A large annotated corpus for learning natural language inference. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP). |
|
- Peter Young, Alice Lai, Micah Hodosh, and Julia Hockenmaier. "From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions." Transactions of the Association for Computational Linguistics 2 (2014): 67-78. |
|
""" |
|
|
|
_DESCRIPTION = """\ |
|
== 日本語SNLI(JSNLI)データセット == |
|
|
|
SNLI コーパスを日本語に翻訳した自然言語推論データセット |
|
学習データは元データを翻訳し、計算機によるフィルタリングによって作成 |
|
評価データは日本語として意味が通るか、翻訳後のラベルが元のラベルと一致しているかどうかの2段階のクラウドソーシングによりデータをフィルタリング |
|
""" |
|
|
|
_HOMEPAGE = "https://nlp.ist.i.kyoto-u.ac.jp/?%E6%97%A5%E6%9C%AC%E8%AA%9ESNLI%28JSNLI%29%E3%83%87%E3%83%BC%E3%82%BF%E3%82%BB%E3%83%83%E3%83%88" |
|
|
|
_LICENSE = """\ |
|
CC BY-SA 4.0 |
|
""" |
|
|
|
_URL = "https://nlp.ist.i.kyoto-u.ac.jp/DLcounter/lime.cgi?down=https://nlp.ist.i.kyoto-u.ac.jp/nl-resource/JSNLI/jsnli_1.1.zip&name=JSNLI.zip" |
|
|
|
|
|
class JSNLIDataset(ds.GeneratorBasedBuilder): |
|
VERSION = ds.Version("1.1.0") |
|
|
|
BUILDER_CONFIGS = [ |
|
ds.BuilderConfig( |
|
name="with-filtering", |
|
version=VERSION, |
|
description="SNLIの学習データに機械翻訳を適用した後、BLEUスコアの閾値0.1でフィルタリングを施したもの。BERTにこの学習データを学習させることにより、93.0%の精度を記録した。(533,005ペア)", |
|
), |
|
ds.BuilderConfig( |
|
name="without-filtering", |
|
version=VERSION, |
|
description="SNLIの学習データに機械翻訳を適用したもの。フィルタリングは行っていない。(548,014ペア)", |
|
), |
|
] |
|
|
|
def _info(self) -> ds.DatasetInfo: |
|
features = ds.Features( |
|
{ |
|
"premise": ds.Value("string"), |
|
"hypothesis": ds.Value("string"), |
|
"label": ds.ClassLabel( |
|
names=["entailment", "neutral", "contradiction"] |
|
), |
|
} |
|
) |
|
return ds.DatasetInfo( |
|
description=_DESCRIPTION, |
|
features=features, |
|
homepage=_HOMEPAGE, |
|
license=_LICENSE, |
|
citation=_CITATION, |
|
) |
|
|
|
def _split_generators(self, dl_manager: ds.DownloadManager): |
|
jsnli_base_dir = dl_manager.download_and_extract(_URL) |
|
jsnli_dir = os.path.join( |
|
jsnli_base_dir, f"jsnli_{self.VERSION.major}.{self.VERSION.minor}" |
|
) |
|
|
|
train_w_filtering_path = os.path.join(jsnli_dir, "train_w_filtering.tsv") |
|
train_wo_filtering_path = os.path.join(jsnli_dir, "train_wo_filtering.tsv") |
|
|
|
dev_path = os.path.join(jsnli_dir, "dev.tsv") |
|
if "with-filtering" in self.config.name: |
|
tng_path = train_w_filtering_path |
|
elif "without-filtering" in self.config.name: |
|
tng_path = train_wo_filtering_path |
|
else: |
|
raise ValueError(f"Invalid config name: {self.config.name}") |
|
|
|
tng_gen_kwargs = { |
|
"tsv_path": tng_path, |
|
} |
|
val_gen_kwargs = { |
|
"tsv_path": dev_path, |
|
} |
|
|
|
return [ |
|
ds.SplitGenerator( |
|
name=ds.Split.TRAIN, |
|
gen_kwargs=tng_gen_kwargs, |
|
), |
|
ds.SplitGenerator( |
|
name=ds.Split.VALIDATION, |
|
gen_kwargs=val_gen_kwargs, |
|
), |
|
] |
|
|
|
def _generate_examples( |
|
self, |
|
tsv_path: str, |
|
): |
|
with open(tsv_path, "r") as rf: |
|
for sentence_id, line in enumerate(rf): |
|
label, premise, hypothesis = line.replace("\n", "").split("\t") |
|
|
|
example_dict = { |
|
"premise": premise, |
|
"hypothesis": hypothesis, |
|
"label": label, |
|
} |
|
yield sentence_id, example_dict |
|
|
