File size: 3,302 Bytes
0cb5e79
 
 
 
 
 
 
15e6797
 
0cb5e79
 
 
15e6797
c78458f
 
 
15e6797
c78458f
 
 
0cb5e79
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
language:
- it
language_details: it-IT
license: cc-by-nc-sa-4.0
task_categories:
- question-answering
task_ids:
- text-classification
configs:
- config_name: default
  data_files:
  - split: test_1
    path: "multichoice_v1_test.jsonl"
  - split: dev_1
    path: "multichoice_v1_dev.jsonl"
  - split: test_2
    path: "multichoice_v2_test.jsonl"
  - split: dev_2
    path: "multichoice_v2_dev.jsonl"
size_categories:
- n<1K
---

### QA4FAQ @ EVALITA 2016

Original dataset information available [here](http://qa4faq.github.io/)



## Data format

The data has been converted to be used as a questin answering task.
There are two splits, test-1 and test-2, each containing the same data processed in slightly different ways.

### test-1
The data is in jsonl format, where each line is a json object with the following fields:
- `id`: a unique identifier for the question
- `question`: the question
- `A`, `B`, `C`, `D`: the possible answers to the question
- `correct_answer`: correct answer to the question ('A', 'B', 'C', 'D')

wrong answers are randomly drawn from the other question, answers pairs in the dataset.

### test-2
The data is in jsonl format, where each line is a json object with the following fields:
- `id`: a unique identifier for the question
- `question`: the question
- `A`, `B`, `C`, `D`: the possible question,answers pairs e.g. (question, answer)
- `correct_answer`: correct question,answer pair to the question ('A', 'B', 'C', 'D') 

wrong (q,a) pairs are randomly created by randomy choosing answers from the dataset. 



## Publications
```
@inproceedings{agirre-etal-2015-semeval,
    title = "{S}em{E}val-2015 Task 2: Semantic Textual Similarity, {E}nglish, {S}panish and Pilot on Interpretability",
    author = "Agirre, Eneko  and
      Banea, Carmen  and
      Cardie, Claire  and
      Cer, Daniel  and
      Diab, Mona  and
      Gonzalez-Agirre, Aitor  and
      Guo, Weiwei  and
      Lopez-Gazpio, I{\~n}igo  and
      Maritxalar, Montse  and
      Mihalcea, Rada  and
      Rigau, German  and
      Uria, Larraitz  and
      Wiebe, Janyce",
    editor = "Nakov, Preslav  and
      Zesch, Torsten  and
      Cer, Daniel  and
      Jurgens, David",
    booktitle = "Proceedings of the 9th International Workshop on Semantic Evaluation ({S}em{E}val 2015)",
    month = jun,
    year = "2015",
    address = "Denver, Colorado",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/S15-2045",
    doi = "10.18653/v1/S15-2045",
    pages = "252--263",
}
```

```
@inproceedings{nakov-etal-2015-semeval,
    title = "{S}em{E}val-2015 Task 3: Answer Selection in Community Question Answering",
    author = "Nakov, Preslav  and
      M{\`a}rquez, Llu{\'\i}s  and
      Magdy, Walid  and
      Moschitti, Alessandro  and
      Glass, Jim  and
      Randeree, Bilal",
    editor = "Nakov, Preslav  and
      Zesch, Torsten  and
      Cer, Daniel  and
      Jurgens, David",
    booktitle = "Proceedings of the 9th International Workshop on Semantic Evaluation ({S}em{E}val 2015)",
    month = jun,
    year = "2015",
    address = "Denver, Colorado",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/S15-2047",
    doi = "10.18653/v1/S15-2047",
    pages = "269--281",
}

```