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import json
import datasets
logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """[ConceptNet with high confidence](https://home.ttic.edu/~kgimpel/commonsense.html)"""
_NAME = "conceptnet_relational_similarity"
_VERSION = "3.0.1"
_CITATION = """
@inproceedings{li-16,
title = {Commonsense Knowledge Base Completion},
author = {Xiang Li and Aynaz Taheri and Lifu Tu and Kevin Gimpel},
booktitle = {Proc. of ACL},
year = {2016}
}
@InProceedings{P16-1137,
author = "Li, Xiang
and Taheri, Aynaz
and Tu, Lifu
and Gimpel, Kevin",
title = "Commonsense Knowledge Base Completion",
booktitle = "Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) ",
year = "2016",
publisher = "Association for Computational Linguistics",
pages = "1445--1455",
location = "Berlin, Germany",
doi = "10.18653/v1/P16-1137",
url = "http://aclweb.org/anthology/P16-1137"
}
"""
_HOME_PAGE = "https://github.com/asahi417/relbert"
_URL = f'https://huggingface.co/datasets/relbert/{_NAME}/resolve/main/dataset'
_URLS = {
str(datasets.Split.TRAIN): [f'{_URL}/train.jsonl'],
str(datasets.Split.VALIDATION): [f'{_URL}/valid.jsonl'],
str(datasets.Split.TEST): [f'{_URL}/test.jsonl'],
}
class ConceptNetRelationalSimilarityConfig(datasets.BuilderConfig):
"""BuilderConfig"""
def __init__(self, **kwargs):
"""BuilderConfig.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(ConceptNetRelationalSimilarityConfig, self).__init__(**kwargs)
class ConceptNetRelationalSimilarity(datasets.GeneratorBasedBuilder):
"""Dataset."""
BUILDER_CONFIGS = [
ConceptNetRelationalSimilarityConfig(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=i, gen_kwargs={"filepaths": downloaded_file[i]}) for i in _URLS.keys()]
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(
{
"relation_type": datasets.Value("string"),
"positives": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
"negatives": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
}
),
supervised_keys=None,
homepage=_HOME_PAGE,
citation=_CITATION,
)
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