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import json
import datasets
logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """Dataset for relation mapping task (see [paper](https://arxiv.org/abs/2211.15268))."""
_NAME = "scientific_and_creative_analogy"
_VERSION = "0.0.0"
_CITATION = """
@article{czinczoll2022scientific,
title={Scientific and Creative Analogies in Pretrained Language Models},
author={Czinczoll, Tamara and Yannakoudakis, Helen and Mishra, Pushkar and Shutova, Ekaterina},
journal={arXiv preprint arXiv:2211.15268},
year={2022}
}
"""
_HOME_PAGE = "https://github.com/taczin/SCAN_analogies"
_URLS = {
str(datasets.Split.TEST): [f'https://huggingface.co/datasets/relbert/{_NAME}/raw/main/data.jsonl']
}
class ScientificAndCreativeAnalogyConfig(datasets.BuilderConfig):
"""BuilderConfig"""
def __init__(self, **kwargs):
"""BuilderConfig.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(ScientificAndCreativeAnalogyConfig, self).__init__(**kwargs)
class ScientificAndCreativeAnalogy(datasets.GeneratorBasedBuilder):
"""Dataset."""
BUILDER_CONFIGS = [
ScientificAndCreativeAnalogyConfig(name=_NAME, version=datasets.Version(_VERSION), description=_DESCRIPTION),
]
def _split_generators(self, dl_manager):
downloaded_file = dl_manager.download_and_extract(_URLS)
return [datasets.SplitGenerator(
name=str(datasets.Split.TEST), gen_kwargs={"filepaths": downloaded_file[str(datasets.Split.TEST)]})
]
def _generate_examples(self, filepaths):
_key = 0
for filepath in filepaths:
logger.info(f"generating examples from = {filepath}")
with open(filepath, encoding="utf-8") as f:
_list = [i for i in f.read().split('\n') if len(i) > 0]
for i in _list:
data = json.loads(i)
yield _key, data
_key += 1
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"id": datasets.Value("string"),
"type": datasets.Value("string"),
"reference": datasets.Sequence(datasets.Value("string")),
"source": datasets.Sequence(datasets.Value("string")),
"target": datasets.Sequence(datasets.Value("string")),
"target_random": datasets.Sequence(datasets.Value("string")),
}
),
supervised_keys=None,
homepage=_HOME_PAGE,
citation=_CITATION,
)
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