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import json
import datasets
logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """[SemEVAL 2012 task 2: Relational Similarity](https://aclanthology.org/S12-1047/)"""
_NAME = "semeval2012_relational_similarity"
_VERSION = "0.0.1"
_CITATION = """
@inproceedings{jurgens-etal-2012-semeval,
title = "{S}em{E}val-2012 Task 2: Measuring Degrees of Relational Similarity",
author = "Jurgens, David and
Mohammad, Saif and
Turney, Peter and
Holyoak, Keith",
booktitle = "*{SEM} 2012: The First Joint Conference on Lexical and Computational Semantics {--} Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation ({S}em{E}val 2012)",
month = "7-8 " # jun,
year = "2012",
address = "Montr{\'e}al, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S12-1047",
pages = "356--364",
}
"""
_HOME_PAGE = "https://github.com/asahi417/relbert"
_URL = f'https://huggingface.co/datasets/relbert/{_NAME}/resolve/main/data'
_URLS = {
str(datasets.Split.TRAIN): [f'{_URL}/train.jsonl'],
str(datasets.Split.VALIDATION): [f'{_URL}/valid.jsonl'],
}
class SemEVAL2012RelationalSimilarityConfig(datasets.BuilderConfig):
"""BuilderConfig"""
def __init__(self, **kwargs):
"""BuilderConfig.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(SemEVAL2012RelationalSimilarityConfig, self).__init__(**kwargs)
class SemEVAL2012RelationalSimilarity(datasets.GeneratorBasedBuilder):
"""Dataset."""
BUILDER_CONFIGS = [
SemEVAL2012RelationalSimilarityConfig(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[str(i)]})
for i in [datasets.Split.TRAIN, datasets.Split.VALIDATION]]
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,
) |