Datasets:
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import datasets
# import pandas as pd
import json
_CITATION = """\
@inproceedings{li-etal-2022-cm,
title = "{CM}-Gen: A Neural Framework for {C}hinese Metaphor Generation with Explicit Context Modelling",
author = "Li, Yucheng and
Lin, Chenghua and
Guerin, Frank",
booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2022.coling-1.563",
pages = "6468--6479",
}
@misc{li-inlg-2022-nominal,
doi = {10.48550/ARXIV.2206.05195},
url = {https://arxiv.org/abs/2206.05195},
author = {Li, Yucheng and Lin, Chenghua and Geurin, Frank},
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Nominal Metaphor Generation with Multitask Learning},
publisher = {arXiv},
year = {2022},
copyright = {arXiv.org perpetual, non-exclusive license}
}
"""
_DESCRIPTION = """\
Chinese Metaphor Corpus
The first Chinese metaphor corpus serving both metaphor identification and generation.
首个中文比喻数据集，可以用于中文比喻识别与中文比喻生成。
"""
_HOMEPAGE = "https://github.com/liyucheng09/Metaphor_Generator"
_URL = 'https://github.com/liyucheng09/Metaphor_Generator/raw/master/CMC/zh_CMC2.txt'
class CMC(datasets.GeneratorBasedBuilder):
BUILDER_CONFIG_CLASS=datasets.BuilderConfig
def _info(self):
feature = {
'sent': datasets.Value('string'),
'tenor': datasets.Value('string'),
'comparator': datasets.Value('string'),
'vehicle':datasets.Value('string'),
}
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(feature),
homepage=_HOMEPAGE,
citation=_CITATION
)
def _split_generators(self, dl_manager):
cmc_file = dl_manager.download(_URL)
return datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'cmc_file': cmc_file}),
# return [
# datasets.SplitGenerator(name='hard', gen_kwargs={'filepath': self.config.data_path}),
# ]
def _generate_examples(self, cmc_file):
with open(cmc_file, encoding='utf-8') as f:
count = 0
for line in f:
if not line:
continue
data = json.loads(line)
yield count, {
'sent': data['sent'],
'tenor': data['tenor'],
'comparator': data['comparator'],
'vehicle': data['vehicle']
}
count+=1 |