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Browse files- README.md +364 -0
- en-as/test-00000-of-00001.parquet +3 -0
- en-bn/test-00000-of-00001.parquet +3 -0
- en-gu/test-00000-of-00001.parquet +3 -0
- en-hi/test-00000-of-00001.parquet +3 -0
- en-kn/test-00000-of-00001.parquet +3 -0
- en-ml/test-00000-of-00001.parquet +3 -0
- en-mr/test-00000-of-00001.parquet +3 -0
- en-or/test-00000-of-00001.parquet +3 -0
- en-pa/test-00000-of-00001.parquet +3 -0
- en-ta/test-00000-of-00001.parquet +3 -0
- en-te/test-00000-of-00001.parquet +3 -0
- en-ur/test-00000-of-00001.parquet +3 -0
README.md
ADDED
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1 |
+
---
|
2 |
+
annotations_creators:
|
3 |
+
- crowdsourced
|
4 |
+
language_creators:
|
5 |
+
- crowdsourced
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6 |
+
- found
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7 |
+
- machine-generated
|
8 |
+
language:
|
9 |
+
- as
|
10 |
+
- bn
|
11 |
+
- en
|
12 |
+
- gu
|
13 |
+
- hi
|
14 |
+
- kn
|
15 |
+
- ml
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16 |
+
- mr
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17 |
+
- or
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18 |
+
- pa
|
19 |
+
- ta
|
20 |
+
- te
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21 |
+
- ur
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22 |
+
license:
|
23 |
+
- cc0-1.0
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24 |
+
multilinguality:
|
25 |
+
- multilingual
|
26 |
+
size_categories:
|
27 |
+
- 1K<n<10K
|
28 |
+
task_categories:
|
29 |
+
- text-classification
|
30 |
+
task_ids:
|
31 |
+
- text-scoring
|
32 |
+
- semantic-similarity-scoring
|
33 |
+
pretty_name: Indic STS
|
34 |
+
dataset_info:
|
35 |
+
- config_name: en-as
|
36 |
+
features:
|
37 |
+
- name: lang_code
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38 |
+
dtype: string
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39 |
+
- name: source
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40 |
+
dtype: string
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41 |
+
- name: english_sentence
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42 |
+
dtype: string
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43 |
+
- name: indic_sentence
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44 |
+
dtype: string
|
45 |
+
- name: score
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46 |
+
dtype: float64
|
47 |
+
splits:
|
48 |
+
- name: test
|
49 |
+
num_bytes: 167751
|
50 |
+
num_examples: 656
|
51 |
+
download_size: 83024
|
52 |
+
dataset_size: 167751
|
53 |
+
- config_name: en-bn
|
54 |
+
features:
|
55 |
+
- name: lang_code
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56 |
+
dtype: string
|
57 |
+
- name: source
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58 |
+
dtype: string
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+
- name: english_sentence
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+
dtype: string
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+
- name: indic_sentence
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+
dtype: string
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+
- name: score
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+
dtype: float64
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+
splits:
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+
- name: test
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+
num_bytes: 280422
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+
num_examples: 957
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69 |
+
download_size: 133859
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70 |
+
dataset_size: 280422
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+
- config_name: en-gu
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72 |
+
features:
|
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+
- name: lang_code
|
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+
dtype: string
|
75 |
+
- name: source
|
76 |
+
dtype: string
|
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+
- name: english_sentence
|
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+
dtype: string
|
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+
- name: indic_sentence
|
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+
dtype: string
|
81 |
+
- name: score
|
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+
dtype: float64
|
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+
splits:
|
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+
- name: test
|
85 |
+
num_bytes: 217276
|
86 |
+
num_examples: 780
|
87 |
+
download_size: 105617
|
88 |
+
dataset_size: 217276
|
89 |
+
- config_name: en-hi
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90 |
+
features:
|
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+
- name: lang_code
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+
dtype: string
|
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+
- name: source
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+
dtype: string
|
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+
- name: english_sentence
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+
dtype: string
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+
- name: indic_sentence
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+
dtype: string
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+
- name: score
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+
dtype: float64
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+
splits:
|
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+
- name: test
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+
num_bytes: 458019
|
104 |
+
num_examples: 1268
|
105 |
+
download_size: 224825
|
106 |
+
dataset_size: 458019
|
107 |
+
- config_name: en-kn
|
108 |
+
features:
|
109 |
+
- name: lang_code
|
110 |
+
dtype: string
|
111 |
+
- name: source
|
112 |
+
dtype: string
|
113 |
+
- name: english_sentence
|
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+
dtype: string
|
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+
- name: indic_sentence
|
116 |
+
dtype: string
|
117 |
+
- name: score
|
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+
dtype: float64
|
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+
splits:
|
120 |
+
- name: test
|
121 |
+
num_bytes: 291586
|
122 |
+
num_examples: 953
|
123 |
+
download_size: 140273
|
124 |
+
dataset_size: 291586
|
125 |
+
- config_name: en-ml
|
126 |
+
features:
|
127 |
+
- name: lang_code
|
128 |
+
dtype: string
|
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+
- name: source
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+
dtype: string
|
131 |
+
- name: english_sentence
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+
dtype: string
|
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+
- name: indic_sentence
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+
dtype: string
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+
- name: score
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+
dtype: float64
|
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+
splits:
|
138 |
+
- name: test
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139 |
+
num_bytes: 302856
|
140 |
+
num_examples: 947
|
141 |
+
download_size: 139777
|
142 |
+
dataset_size: 302856
|
143 |
+
- config_name: en-mr
|
144 |
+
features:
|
145 |
+
- name: lang_code
|
146 |
+
dtype: string
|
147 |
+
- name: source
|
148 |
+
dtype: string
|
149 |
+
- name: english_sentence
|
150 |
+
dtype: string
|
151 |
+
- name: indic_sentence
|
152 |
+
dtype: string
|
153 |
+
- name: score
|
154 |
+
dtype: float64
|
155 |
+
splits:
|
156 |
+
- name: test
|
157 |
+
num_bytes: 253059
|
158 |
+
num_examples: 779
|
159 |
+
download_size: 124599
|
160 |
+
dataset_size: 253059
|
161 |
+
- config_name: en-or
|
162 |
+
features:
|
163 |
+
- name: lang_code
|
164 |
+
dtype: string
|
165 |
+
- name: source
|
166 |
+
dtype: string
|
167 |
+
- name: english_sentence
|
168 |
+
dtype: string
|
169 |
+
- name: indic_sentence
|
170 |
+
dtype: string
|
171 |
+
- name: score
|
172 |
+
dtype: float64
|
173 |
+
splits:
|
174 |
+
- name: test
|
175 |
+
num_bytes: 121019
|
176 |
+
num_examples: 500
|
177 |
+
download_size: 57149
|
178 |
+
dataset_size: 121019
|
179 |
+
- config_name: en-pa
|
180 |
+
features:
|
181 |
+
- name: lang_code
|
182 |
+
dtype: string
|
183 |
+
- name: source
|
184 |
+
dtype: string
|
185 |
+
- name: english_sentence
|
186 |
+
dtype: string
|
187 |
+
- name: indic_sentence
|
188 |
+
dtype: string
|
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+
- name: score
|
190 |
+
dtype: float64
|
191 |
+
splits:
|
192 |
+
- name: test
|
193 |
+
num_bytes: 204730
|
194 |
+
num_examples: 688
|
195 |
+
download_size: 102251
|
196 |
+
dataset_size: 204730
|
197 |
+
- config_name: en-ta
|
198 |
+
features:
|
199 |
+
- name: lang_code
|
200 |
+
dtype: string
|
201 |
+
- name: source
|
202 |
+
dtype: string
|
203 |
+
- name: english_sentence
|
204 |
+
dtype: string
|
205 |
+
- name: indic_sentence
|
206 |
+
dtype: string
|
207 |
+
- name: score
|
208 |
+
dtype: float64
|
209 |
+
splits:
|
210 |
+
- name: test
|
211 |
+
num_bytes: 368438
|
212 |
+
num_examples: 1044
|
213 |
+
download_size: 162846
|
214 |
+
dataset_size: 368438
|
215 |
+
- config_name: en-te
|
216 |
+
features:
|
217 |
+
- name: lang_code
|
218 |
+
dtype: string
|
219 |
+
- name: source
|
220 |
+
dtype: string
|
221 |
+
- name: english_sentence
|
222 |
+
dtype: string
|
223 |
+
- name: indic_sentence
|
224 |
+
dtype: string
|
225 |
+
- name: score
|
226 |
+
dtype: float64
|
227 |
+
splits:
|
228 |
+
- name: test
|
229 |
+
num_bytes: 291129
|
230 |
+
num_examples: 948
|
231 |
+
download_size: 138528
|
232 |
+
dataset_size: 291129
|
233 |
+
- config_name: en-ur
|
234 |
+
features:
|
235 |
+
- name: lang_code
|
236 |
+
dtype: string
|
237 |
+
- name: source
|
238 |
+
dtype: string
|
239 |
+
- name: english_sentence
|
240 |
+
dtype: string
|
241 |
+
- name: indic_sentence
|
242 |
+
dtype: string
|
243 |
+
- name: score
|
244 |
+
dtype: float64
|
245 |
+
splits:
|
246 |
+
- name: test
|
247 |
+
num_bytes: 150870
|
248 |
+
num_examples: 500
|
249 |
+
download_size: 85405
|
250 |
+
dataset_size: 150870
|
251 |
+
configs:
|
252 |
+
- config_name: en-as
|
253 |
+
data_files:
|
254 |
+
- split: test
|
255 |
+
path: en-as/test-*
|
256 |
+
- config_name: en-bn
|
257 |
+
data_files:
|
258 |
+
- split: test
|
259 |
+
path: en-bn/test-*
|
260 |
+
- config_name: en-gu
|
261 |
+
data_files:
|
262 |
+
- split: test
|
263 |
+
path: en-gu/test-*
|
264 |
+
- config_name: en-hi
|
265 |
+
data_files:
|
266 |
+
- split: test
|
267 |
+
path: en-hi/test-*
|
268 |
+
- config_name: en-kn
|
269 |
+
data_files:
|
270 |
+
- split: test
|
271 |
+
path: en-kn/test-*
|
272 |
+
- config_name: en-ml
|
273 |
+
data_files:
|
274 |
+
- split: test
|
275 |
+
path: en-ml/test-*
|
276 |
+
- config_name: en-mr
|
277 |
+
data_files:
|
278 |
+
- split: test
|
279 |
+
path: en-mr/test-*
|
280 |
+
- config_name: en-or
|
281 |
+
data_files:
|
282 |
+
- split: test
|
283 |
+
path: en-or/test-*
|
284 |
+
- config_name: en-pa
|
285 |
+
data_files:
|
286 |
+
- split: test
|
287 |
+
path: en-pa/test-*
|
288 |
+
- config_name: en-ta
|
289 |
+
data_files:
|
290 |
+
- split: test
|
291 |
+
path: en-ta/test-*
|
292 |
+
- config_name: en-te
|
293 |
+
data_files:
|
294 |
+
- split: test
|
295 |
+
path: en-te/test-*
|
296 |
+
- config_name: en-ur
|
297 |
+
data_files:
|
298 |
+
- split: test
|
299 |
+
path: en-ur/test-*
|
300 |
+
tags:
|
301 |
+
- multilingual
|
302 |
+
- semantic-textual-similarity
|
303 |
+
---
|
304 |
+
|
305 |
+
# Dataset Card for Indic STS
|
306 |
+
|
307 |
+
This dataset is STS benchmark between English and 12 high-resource Indic languages. This was released as a part of [Samanantar](https://arxiv.org/abs/2104.05596) paper. Please refer to the paper for more details.
|
308 |
+
|
309 |
+
### Languages
|
310 |
+
Available languages are: en-as, en-bn, en-gu, en-hi, en-kn, en-ml, en-mr, en-or, en-pa, en-ta, en-te, en-ur
|
311 |
+
|
312 |
+
### Dataset Structure
|
313 |
+
|
314 |
+
#### Dataset Fields
|
315 |
+
|
316 |
+
- lang_code: 2-digit ISO language code
|
317 |
+
- source: The source from which the candidate sentence is considered.
|
318 |
+
- english_sentence: The full sentence in the English language.
|
319 |
+
- indic_sentence: The full sentence in the corresponding Indic language.
|
320 |
+
- score: The similarity score as a float which is <= 5.0 and >= 0.0.
|
321 |
+
|
322 |
+
#### Data Instances
|
323 |
+
|
324 |
+
```json
|
325 |
+
{
|
326 |
+
"lang_code":"hi",
|
327 |
+
"source":"CatchNews",
|
328 |
+
"english_sentence":"\"...this is only an interim measure and as long as we have hopefully control over COVID in a few months or a year\\'s time then I think things will go back to as normal as it can be,\" Kumble said\n",
|
329 |
+
"indic_sentence":"उन्होंने कहा,\"यह केवल एक अंतरिम उपाय है और जब तक हम कुछ महीनों या एक साल के समय में COVID-19 पर नियंत्रण करते हैं, तब तक मुझे लगता है कि चीजें फिर से सामान्य हो जाएंगी\n",
|
330 |
+
"score":4.0
|
331 |
+
}
|
332 |
+
```
|
333 |
+
|
334 |
+
#### Splits
|
335 |
+
|
336 |
+
| | en-as | en-bn | en-gu | en-hi | en-kn | en-ml | en-mr | en-or | en-pa | en-ta | en-te | en-ur |
|
337 |
+
|------|-------|-------|-------|-------|-------|-------|-------|-------|-------|-------|-------|-------|
|
338 |
+
| test | 656 | 957 | 780 | 1268 | 953 | 947 | 779 | 500 | 688 | 1044 | 948 | 500 |
|
339 |
+
|
340 |
+
### Examples of Use
|
341 |
+
|
342 |
+
```python3
|
343 |
+
from datasets import load_dataset
|
344 |
+
dataset = load_dataset("ai4bharat/indic_sts", name="en-hi", split="test")
|
345 |
+
```
|
346 |
+
|
347 |
+
|
348 |
+
### Citation
|
349 |
+
|
350 |
+
```bibtex
|
351 |
+
@article{DBLP:journals/tacl/RameshDBJASSDJK22,
|
352 |
+
author = {Gowtham Ramesh and Sumanth Doddapaneni and Aravinth Bheemaraj and Mayank Jobanputra and Raghavan AK and Ajitesh Sharma and Sujit Sahoo and Harshita Diddee and Mahalakshmi J and Divyanshu Kakwani and Navneet Kumar and Aswin Pradeep and Srihari Nagaraj and Deepak Kumar and Vivek Raghavan and Anoop Kunchukuttan and Pratyush Kumar and Mitesh Shantadevi Khapra},
|
353 |
+
title = {Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages},
|
354 |
+
journal = {Trans. Assoc. Comput. Linguistics},
|
355 |
+
volume = {10},
|
356 |
+
pages = {145-162},
|
357 |
+
year = {2022},
|
358 |
+
url = {https://doi.org/10.1162/tacl\_a\_00452},
|
359 |
+
doi = {10.1162/TACL\_A\_00452},
|
360 |
+
timestamp = {Wed, 29 Jun 2022 16:03:22 +0200},
|
361 |
+
biburl = {https://dblp.org/rec/journals/tacl/RameshDBJASSDJK22.bib},
|
362 |
+
bibsource = {dblp computer science bibliography, https://dblp.org}
|
363 |
+
}
|
364 |
+
```
|
en-as/test-00000-of-00001.parquet
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en-ta/test-00000-of-00001.parquet
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size 85405
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