File size: 4,585 Bytes
a8c1391
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
from dataclasses import dataclass
from enum import Enum
import datasets
from types import SimpleNamespace


BigBioValues = SimpleNamespace(NULL="<BB_NULL_STR>")


@dataclass
class BigBioConfig(datasets.BuilderConfig):
    """BuilderConfig for BigBio."""

    name: str = None
    version: datasets.Version = None
    description: str = None
    schema: str = None
    subset_id: str = None


class Tasks(Enum):
    NAMED_ENTITY_RECOGNITION = "NER"
    NAMED_ENTITY_DISAMBIGUATION = "NED"
    EVENT_EXTRACTION = "EE"
    RELATION_EXTRACTION = "RE"
    COREFERENCE_RESOLUTION = "COREF"
    QUESTION_ANSWERING = "QA"
    TEXTUAL_ENTAILMENT = "TE"
    SEMANTIC_SIMILARITY = "STS"
    TEXT_PAIRS_CLASSIFICATION = "TXT2CLASS"
    PARAPHRASING = "PARA"
    TRANSLATION = "TRANSL"
    SUMMARIZATION = "SUM"
    TEXT_CLASSIFICATION = "TXTCLASS"


entailment_features = datasets.Features(
    {
        "id": datasets.Value("string"),
        "premise": datasets.Value("string"),
        "hypothesis": datasets.Value("string"),
        "label": datasets.Value("string"),
    }
)

pairs_features = datasets.Features(
    {
        "id": datasets.Value("string"),
        "document_id": datasets.Value("string"),
        "text_1": datasets.Value("string"),
        "text_2": datasets.Value("string"),
        "label": datasets.Value("string"),
    }
)

qa_features = datasets.Features(
    {
        "id": datasets.Value("string"),
        "question_id": datasets.Value("string"),
        "document_id": datasets.Value("string"),
        "question": datasets.Value("string"),
        "type": datasets.Value("string"),
        "choices": [datasets.Value("string")],
        "context": datasets.Value("string"),
        "answer": datasets.Sequence(datasets.Value("string")),
    }
)

text_features = datasets.Features(
    {
        "id": datasets.Value("string"),
        "document_id": datasets.Value("string"),
        "text": datasets.Value("string"),
        "labels": [datasets.Value("string")],
    }
)

text2text_features = datasets.Features(
    {
        "id": datasets.Value("string"),
        "document_id": datasets.Value("string"),
        "text_1": datasets.Value("string"),
        "text_2": datasets.Value("string"),
        "text_1_name": datasets.Value("string"),
        "text_2_name": datasets.Value("string"),
    }
)

kb_features = datasets.Features(
    {
        "id": datasets.Value("string"),
        "document_id": datasets.Value("string"),
        "passages": [
            {
                "id": datasets.Value("string"),
                "type": datasets.Value("string"),
                "text": datasets.Sequence(datasets.Value("string")),
                "offsets": datasets.Sequence([datasets.Value("int32")]),
            }
        ],
        "entities": [
            {
                "id": datasets.Value("string"),
                "type": datasets.Value("string"),
                "text": datasets.Sequence(datasets.Value("string")),
                "offsets": datasets.Sequence([datasets.Value("int32")]),
                "normalized": [
                    {
                        "db_name": datasets.Value("string"),
                        "db_id": datasets.Value("string"),
                    }
                ],
            }
        ],
        "events": [
            {
                "id": datasets.Value("string"),
                "type": datasets.Value("string"),
                # refers to the text_bound_annotation of the trigger
                "trigger": {
                    "text": datasets.Sequence(datasets.Value("string")),
                    "offsets": datasets.Sequence([datasets.Value("int32")]),
                },
                "arguments": [
                    {
                        "role": datasets.Value("string"),
                        "ref_id": datasets.Value("string"),
                    }
                ],
            }
        ],
        "coreferences": [
            {
                "id": datasets.Value("string"),
                "entity_ids": datasets.Sequence(datasets.Value("string")),
            }
        ],
        "relations": [
            {
                "id": datasets.Value("string"),
                "type": datasets.Value("string"),
                "arg1_id": datasets.Value("string"),
                "arg2_id": datasets.Value("string"),
                "normalized": [
                    {
                        "db_name": datasets.Value("string"),
                        "db_id": datasets.Value("string"),
                    }
                ],
            }
        ],
    }
)