File size: 1,911 Bytes
32fadfe
 
 
99d6e6d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a0dcc36
 
45b9e85
 
 
a0dcc36
45b9e85
a0dcc36
 
 
 
 
45b9e85
a0dcc36
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
---
license: cc-by-sa-3.0
configs:
- config_name: ara_Arab
  data_files:
  - split: validation
    path: data/ara_Arab/validation*
  - split: test
    path: data/ara_Arab/test*
- config_name: deu_Latn
  data_files:
  - split: validation
    path: data/deu_Latn/validation*
  - split: test
    path: data/deu_Latn/test*
- config_name: eng_Latn
  data_files:
  - split: validation
    path: data/eng_Latn/validation*
  - split: test
    path: data/eng_Latn/test*
- config_name: hin_Deva
  data_files:
  - split: validation
    path: data/hin_Deva/validation*
  - split: test
    path: data/hin_Deva/test*
- config_name: hin_Latn
  data_files:
  - split: validation
    path: data/hin_Latn/validation*
  - split: test
    path: data/hin_Latn/test*
- config_name: spa_Latn
  data_files:
  - split: validation
    path: data/spa_Latn/validation*
  - split: test
    path: data/spa_Latn/test*
- config_name: vie_Latn
  data_files:
  - split: validation
    path: data/vie_Latn/validation*
  - split: test
    path: data/vie_Latn/test*
- config_name: zho_Hans
  data_files:
  - split: validation
    path: data/zho_Hans/validation*
  - split: test
    path: data/zho_Hans/test*
task_categories:
- question-answering
language:
- en
- hi
- ar
- de
- es
- vi
- zh
---

**Source Dataset**    
- Link: [facebook/mlqa](https://huggingface.co/datasets/facebook/mlqa)
- Revision: `397ed406c1a7902140303e7faf60fff35b58d285`

**MLQA**   
MLQA (MultiLingual Question Answering) is a benchmark dataset for evaluating cross-lingual question answering performance.
MLQA consists of over 5K extractive QA instances (12K in English) in SQuAD format in seven languages - English, Arabic,
German, Spanish, Hindi, Vietnamese and Simplified Chinese. MLQA is highly parallel, with QA instances parallel between
4 different languages on average.

**MLQA Plus**  
MLQA Plus additionally has hin_Latn data generated using indictrans library.