File size: 5,517 Bytes
3eaa622
 
 
 
 
 
 
 
 
c420f8a
3eaa622
c420f8a
3eaa622
 
 
c420f8a
 
 
 
4f0b3de
 
 
 
3eaa622
 
c4a8309
 
3eaa622
fd061f3
3eaa622
 
fd061f3
3eaa622
 
fd061f3
3eaa622
 
fd061f3
c420f8a
3eaa622
fd061f3
c420f8a
3eaa622
fd061f3
c420f8a
c4a8309
 
3eaa622
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
e4d37f4
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ecbbce3
 
e4d37f4
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d6323de
 
 
 
 
 
e4d37f4
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
---
dataset_info:
  features:
  - name: transcription
    dtype: string
  - name: glosses
    dtype: string
  - name: translation
    dtype: string
  - name: glottocode
    dtype: string
  - name: id
    dtype: string
  - name: source
    dtype: string
  - name: metalang_glottocode
    dtype: string
  - name: is_segmented
    dtype: string
  - name: language
    dtype: string
  - name: metalang
    dtype: string
  splits:
  - name: train
    num_bytes: 93769783
    num_examples: 418718
  - name: train_ID
    num_bytes: 25048415
    num_examples: 104928
  - name: eval_ID
    num_bytes: 2732125
    num_examples: 11138
  - name: test_ID
    num_bytes: 2869258
    num_examples: 11940
  - name: train_OOD
    num_bytes: 1817406
    num_examples: 7356
  - name: eval_OOD
    num_bytes: 249722
    num_examples: 984
  - name: test_OOD
    num_bytes: 240556
    num_examples: 972
  download_size: 38002540
  dataset_size: 126727265
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: train_ID
    path: data/train_ID-*
  - split: eval_ID
    path: data/eval_ID-*
  - split: test_ID
    path: data/test_ID-*
  - split: train_OOD
    path: data/train_OOD-*
  - split: eval_OOD
    path: data/eval_OOD-*
  - split: test_OOD
    path: data/test_OOD-*
---

# Multilingual IGT

<!-- Provide a quick summary of the dataset. -->

A compilation of various sources of interlinear glossed text (IGT) across nearly **two thousand languages** in a standardized format.

## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->



<!-- - **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed] -->
- **License:** CC BY 4.0

### Dataset Sources [optional]

<!-- Provide the basic links for the dataset. -->

- **Repository:** https://github.com/foltaProject/glosslm/settings
- **Paper [optional]:** Coming soon...


### Direct Use

<!-- This section describes suitable use cases for the dataset. -->

- Training models for IGT generation
- Linguistic analysis of IGT across languages
- Use of IGT in downstream applications such as machine translation


## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

[More Information Needed]

## Dataset Creation

### Source Data

<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
- IMTVault 1.1 (https://imtvault.org)
- ODIN (http://depts.washington.edu/uwcl/odin/)
- APiCS (https://apics-online.info)
- UraTyp (https://uralic.clld.org)
- Guarani Corpus (https://guaranicorpus.usc.edu)
- 2023 SIGMORPHON Shared Task (https://github.com/sigmorphon/2023GlossingST)

#### Data Collection and Processing

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->

[More Information Needed]

#### Who are the source data producers?

<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->

[More Information Needed]

### Annotations [optional]

<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->

#### Annotation process

<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->

[More Information Needed]

#### Who are the annotators?

<!-- This section describes the people or systems who created the annotations. -->

[More Information Needed]

#### Personal and Sensitive Information

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->

[More Information Needed]

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

[More Information Needed]

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [optional]

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

[More Information Needed]

**APA:**

[More Information Needed]

## Glossary [optional]

<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->

[More Information Needed]

## More Information [optional]

[More Information Needed]

## Dataset Card Authors [optional]

[More Information Needed]

## Dataset Card Contact

[More Information Needed]