Create defeasible-nli.py

defeasible-nli.py

@@ -0,0 +1,60 @@
+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