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README.md

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----
-license: cc-by-nc-sa-4.0
----

chinese_metaphor_dataset.py

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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

default/chinese_metaphor_dataset-train.parquet

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