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README.md

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----
-license: apache-2.0
----

mega-acceptability-v2.tsv → mega-acceptability-v2/mega-train.parquet

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mega-intensionality-v1-normalized/mega-train.parquet

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mega-negraising-v1-normalized/mega-train.parquet

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mega-orientation-v1.1/mega-train.parquet

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mega-veridicality-v2/mega-train.parquet

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mega.py

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-import datasets
-import csv
-
-
-citation='''
-@article{white2020frequency,
-  title={Frequency, acceptability, and selection: A case study of clause-embedding},
-  author={White, Aaron Steven and Rawlins, Kyle},
-  journal={arXiv preprint arXiv:2004.04106},
-  year={2020}
-}
-'''
-
-class MegaConfig(datasets.BuilderConfig):
-    citation=citation
-
-files = ['mega-acceptability-v2.tsv', 'mega-intensionality-v1-normalized.tsv', 'mega-negraising-v1-normalized.tsv',
-        'mega-orientation-v1.1.tsv', 'mega-veridicality-v2.csv']
-
-_URLs = {f:f"https://huggingface.co/datasets/metaeval/mega/raw/main/{f}" for f in files}
-
-class Mega(datasets.GeneratorBasedBuilder):
-    
-    BUILDER_CONFIGS = [
-            MegaConfig(
-                name='.'.join(n.split('.')[:-1]),
-                data_dir=n
-            ) for n in files
-    ]
-
-    def _split_generators(self, dl_manager: datasets.DownloadManager):
-        data_file = dl_manager.download(_URLs)
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_file[self.config.data_dir]}),
-        ]
-
-    def _info(self):
-        return datasets.DatasetInfo()
-    
-    def _generate_examples(self, filepath):
-        with open(filepath, encoding="utf-8") as f:
-            reader = csv.DictReader(f,delimiter='\t' if '.tsv' in self.config.data_dir else ',')
-            for id_, row in enumerate(reader):
-                if id_ == 0:
-                    continue
-                yield id_, row