Datasets:

License:
File size: 3,919 Bytes
dd19425
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.


import csv
import datasets


_CITATION = """\
@inproceedings{inproceedings,
author = {Ek, Adam and Noble, Bill and Chatzikyriakidis, Stergios and Cooper, Robin and Dobnik, Simon and Gregoromichelaki, Eleni and Howes, Christine and Larsson, Staffan and Maraev, Vladislav and Mills, Gregory and Wijnholds, Gijs},
year = {2024},
month = {08},
pages = {},
title = {I hea-umm think that's what they say: A Dataset of Inferences from Natural Language Dialogues}
}
"""

_DESCRIPTION = """\
DNLI is a dataset for NLI in transcripts of spoken dialogues"""

_HOMEPAGE = "https://github.com/GU-CLASP/DNLI/tree/main"

_LICENSE = "MIT"


_URLS_prefix = {
    "dnli" : "https://github.com/GU-CLASP/DNLI/blob/main/data/compiled"
}
_URLS = {
    "test_1": {
        "test": _URLS_prefix["dnli"] + "/test_1_data.csv"
    },
    "test_2": {
        "test": _URLS_prefix["dnli"] + "/test_2_data.csv"
    },
    "test_3": {
        "test": _URLS_prefix["dnli"] + "/test_3_data.csv"
    },
    "test_4": {
        "test": _URLS_prefix["dnli"] + "/test_4_data.csv"
    },
    "test_5": {
        "test": _URLS_prefix["dnli"] + "/test_5_data.csv"
    },
    "test_6": {
        "test": _URLS_prefix["dnli"] + "/test_6_data.csv"
    },
    "test_7": {
        "test": _URLS_prefix["dnli"] + "/test_7_data.csv"
    },
    "test_8": {
        "test": _URLS_prefix["dnli"] + "/test_8_data.csv"
    },
    "test_9": {
        "test": _URLS_prefix["dnli"] + "/test_9_data.csv"
    },
    "test_10": {
        "test": _URLS_prefix["dnli"] + "/test_10_data.csv"
    },
    "test_11": {
        "test": _URLS_prefix["dnli"] + "/test_11_data.csv"
    },
    "test_12": {
        "test": _URLS_prefix["dnli"] + "/test_12_data.csv"
    },
    "test_13": {
        "test": _URLS_prefix["dnli"] + "/test_13_data.csv"
    },
    "test_14": {
        "test": _URLS_prefix["dnli"] + "/test_14_data.csv"
    },
    "test_15": {
        "test": _URLS_prefix["dnli"] + "/test_15_data.csv"
    },
}



class DNLI(datasets.GeneratorBasedBuilder):
    """ DNLI is a dataset for NLI in transcripts of spoken dialogues
"""

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            name=config_name,
            version=datasets.Version("0.0.1"),
            description=f"{config_name}"
        )
        for config_name in _URLS.keys()
    ]
    def _info(self):
        features = {
            "hypothesis": datasets.Value("string"),
            "premise": datasets.Value("string"),
            "label": datasets.Value("string"),
        }

    def _split_generators(self, dl_manager):
        urls = _URLS[self.config.name]
        data_dir = dl_manager.download_and_extract(urls)
        return [
            datasets.SplitGenerator(
                name = datasets.Split.TEST,
                gen_kwargs = {
                    "filepath" : data_dir["test"],
                    "split" : "test",
                }
            )
        ]

    def _generate_examples(self, filepath, split):
        with open(filepath, encoding="utf-8") as fin:
            reader = csv.reader(fin, delimiter='\t')
            for idx, row in enumerate(reader):
                yield idx, {
                    "hypothesis": row[0],
                    "premise": row[1],
                    "label": row[2]
                }