Datasets:

Modalities:
Text
Libraries:
Datasets
License:
File size: 1,480 Bytes
0c3e6f7
 
 
 
 
 
 
 
 
 
 
 
 
 
f162753
0c3e6f7
 
 
75fb74b
97e9eb4
75fb74b
0c3e6f7
 
 
 
 
 
 
 
 
 
91c9b64
0c3e6f7
a5798a2
0c3e6f7
 
 
 
 
9f76892
 
0c3e6f7
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
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/blob/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