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README.md

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----
-license: apache-2.0
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snli_train.jsonl → atomic/defeasible-nli-test.parquet

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social_train.jsonl → atomic/defeasible-nli-train.parquet

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atomic_train.jsonl → atomic/defeasible-nli-validation.parquet

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defeasible-nli.py

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-import datasets
-import json
-import os
-
-citation='''
-@inproceedings{rudinger-etal-2020-thinking,
-    title = "Thinking Like a Skeptic: Defeasible Inference in Natural Language",
-    author = "Rudinger, Rachel  and
-      Shwartz, Vered  and
-      Hwang, Jena D.  and
-      Bhagavatula, Chandra  and
-      Forbes, Maxwell  and
-      Le Bras, Ronan  and
-      Smith, Noah A.  and
-      Choi, Yejin",
-    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
-    month = nov,
-    year = "2020",
-    address = "Online",
-    publisher = "Association for Computational Linguistics",
-    url = "https://www.aclweb.org/anthology/2020.findings-emnlp.418",
-    doi = "10.18653/v1/2020.findings-emnlp.418",
-    pages = "4661--4675"
-}
-'''
-
-class DefeasibleNLIConfig(datasets.BuilderConfig):
-    citation=citation
-
-configs = ['atomic','snli','social']                                                              
-splits=['train', 'test', 'dev']
-_URLs = {(f,s):f"https://huggingface.co/datasets/metaeval/defeasible-nli/resolve/main/{f}_{s}.jsonl" for f in configs for s in splits}
-
-class DefeasibleNLI(datasets.GeneratorBasedBuilder):
-    
-    BUILDER_CONFIGS = [
-            DefeasibleNLIConfig(
-                name=n,
-                data_dir=n
-            ) for n in configs
-    ]
-
-    def _split_generators(self, dl_manager: datasets.DownloadManager):
-        path = lambda split: dl_manager.download(_URLs[self.config.name,split])
-        return [ datasets.SplitGenerator(name=name, gen_kwargs={'path':path(split),'split':split})
-                for name,split in zip([datasets.Split.TRAIN,datasets.Split.VALIDATION,datasets.Split.TEST],
-                                       ['train','dev','test'])]
-
-    def _info(self):
-        return datasets.DatasetInfo()
-    
-    def _generate_examples(self,path,split):
-        """Yields examples."""
-        with open(path, "r", encoding="utf-8") as f:
-            for id_, line in enumerate(f):
-                line_dict = json.loads(line)
-                if not line_dict['UpdateTypeImpossible']:
-                    fields = ["Premise","Hypothesis","Update","UpdateType"]#,"UpdateTypeImpossible","UpdateTypeImpossibleReason"]
-                    line_dict = {k:v for k,v in line_dict.items() if k in fields}
-                    yield id_, line_dict

snli/defeasible-nli-test.parquet

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snli/defeasible-nli-train.parquet

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snli/defeasible-nli-validation.parquet

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social/defeasible-nli-test.parquet

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social/defeasible-nli-train.parquet

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social/defeasible-nli-validation.parquet

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