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Datasets:
SINAI
/
databenchSPA

Tasks:
Table Question Answering
Question Answering
Modalities:
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Formats:
parquet
Languages:
English
Spanish
Size:
< 1K
Tags:
table-question-answering
table
qa
Libraries:
Datasets
pandas
License:
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1
- ---
2
- language:
3
- - en
4
- - es
5
- pretty_name: "DataBench SPAnish"
6
- tags:
7
- - table-question-answering
8
- - table
9
- - qa
10
- license: mit
11
- task_categories:
12
- - table-question-answering
13
- - question-answering
14
- default: qa
15
- configs:
16
- - config_name: qa
17
- data_files:
18
- - ES_01_40db_Igualdad/qa.parquet
19
- - ES_02_40dB_Dormir/qa.parquet
20
- - ES_03_CIS_Enero_Marzo_2023/qa.parquet
21
- - ES_04_CEA_Barometro_Andaluz_Septiembre_2023/qa.parquet
22
- - ES_05_CIS_2023_Salud_Bienestar/qa.parquet
23
- - ES_06_CIS_Politica_Fiscal_Julio_2023/qa.parquet
24
- - ES_07_CIS_Relaciones_Afectivas_Pospandemia_III/qa.parquet
25
- - ES_08_CIS_Barometro_Diciembre_2022/qa.parquet
26
- - ES_09_40dB_Percepcion_Amor/qa.parquet
27
- - ES_10_CIS_Salud_Mental_Pandemia_2021/qa.parquet
28
- - config_name: iberlef
29
- data_files:
30
- - split: dev
31
- path:
32
- - ES_01_40db_Igualdad/qa.parquet
33
- - ES_02_40dB_Dormir/qa.parquet
34
- - ES_03_CIS_Enero_Marzo_2023/qa.parquet
35
- - ES_04_CEA_Barometro_Andaluz_Septiembre_2023/qa.parquet
36
- - split: train
37
- path:
38
- - ES_05_CIS_2023_Salud_Bienestar/qa.parquet
39
- - ES_06_CIS_Politica_Fiscal_Julio_2023/qa.parquet
40
- - ES_07_CIS_Relaciones_Afectivas_Pospandemia_III/qa.parquet
41
- - ES_08_CIS_Barometro_Diciembre_2022/qa.parquet
42
- - ES_09_40dB_Percepcion_Amor/qa.parquet
43
- - ES_10_CIS_Salud_Mental_Pandemia_2021/qa.parquet
44
- ---
45
-
46
- # DataBench SPAnish
47
-
48
- This repository contains the original 10 datasets used for the paper [Towards Quality Benchmarking in Question Answering over Tabular Data in Spanish](http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6617) which appeared in SEPLN 2024.
49
-
50
- It is a spin-off of the original suite in English, which you can find [here](https://huggingface.co/datasets/cardiffnlp/databench).
51
-
52
-
53
-
54
- ## Usage
55
-
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- ```python
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- from datasets import load_dataset
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-
59
- # Load all QA pairs
60
- all_qa = load_dataset("SINAI/databenchSPA", name="qa")
61
-
62
- # Load PRESTA QA splits
63
- iberlef_train_qa = load_dataset("SINAI/databenchSPA", name="iberlef", split="train")
64
- iberlef_dev_qa = load_dataset("SINAI/databenchSPA", name="iberlef", split="dev")
65
-
66
- ```
67
-
68
- You can use any of the individual [integrated libraries](https://huggingface.co/docs/hub/datasets-libraries#libraries) to load the actual data where the answer is to be retrieved.
69
-
70
- For example, using pandas in Python:
71
-
72
- ```python
73
- import pandas as pd
74
-
75
- # "ES_01_40db_Igualdad", the id of the dataset
76
- ds_id = all_qa['dataset'][0]
77
-
78
- # Dataset containing the answer
79
- df = pd.read_parquet(f"hf://datasets/SINAI/databenchSPA/{ds_id}/all.parquet")
80
- ```
81
-
82
- | # | Name | Rows | Columns | #QA | Source (Reference) |
83
- |----|----------------------------------------------------------------------------------------------------------------------------------------------|-------|---------|-----|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
84
- | 1 | [Encuesta de Igualidad](https://public.graphext.com/bcf11ce000281e77/index.html?section=data) | 2000 | 105 | 20 | [40dB](https://elpais.com/espana/2024-03-11/consulte-todos-los-datos-internos-de-la-encuesta-de-el-pais-de-marzo-cuestionarios-cruces-y-respuestas.html) |
85
- | 2 | [Calidad del Sueño](https://public.graphext.com/d586cf17f68716b2/index.html) | 2000 | 80 | 20 | [40dB](https://elpais.com/ciencia/2024-02-25/consulte-todos-los-datos-internos-del-barometro-de-el-pais-cuestionarios-cruces-y-respuestas-individuales.html) |
86
- | 3 | [Fusión Barómetros](https://public.graphext.com/090bc5693db03f4b/index.html) | 7430 | 161 | 20 | [CIS](https://www.cis.es/es/detalle-ficha-estudio?idEstudio=14707) |
87
- | 4 | [Barómetro Andaluz](https://public.graphext.com/ece62fc1938451e2/index.html) | 5349 | 85 | 20 | [CEA](https://www.centrodeestudiosandaluces.es/barometro/barometro-andaluz-de-septiembre-2023) |
88
- | 5 | [Juventud](https://public.graphext.com/d47edca4181aa6ab/index.html) | 1510 | 236 | 20 | [CRS](https://www.centroreinasofia.org/publicacion/barometro-salud-2023/) |
89
- | 6 | [Política Fiscal](https://public.graphext.com/244aabe0e1f29604/index.html?section=data) | 3011 | 198 | 20 | [CIS](https://www.cis.es/detalle-ficha-estudio?origen=estudio&idEstudio=14741) |
90
- | 7 | [Relaciones](https://public.graphext.com/4bfd99166c878c01/index.html) | 2491 | 186 | 20 | [CIS](https://www.cis.es/detalle-ficha-estudio?origen=estudio&idEstudio=14702) |
91
- | 8 | [Barómetro Mensual](https://public.graphext.com/6d6ed9331ce0ab03/index.html) | 2444 | 185 | 20 | [CIS](https://www.cis.es/es/detalle-ficha-estudio?idEstudio=14676) |
92
- | 9 | [Percepción del Amor](https://public.graphext.com/0c073fc60827634b/index.html?section=data) | 2000 | 150 | 20 | [40dB](https://elpais.com/sociedad/2022-06-05/consulte-todos-los-datos-internos-de-la-encuesta-de-el-pais-sobre-la-percepcion-del-amor-cuestionarios-y-respuestas-individuales.html) |
93
- | 10 | [Salud Mental](https://public.graphext.com/05917cf2424e681f/index.html?section=data) | 3083 | 354 | 20 | [CIS](https://datos.gob.es/es/catalogo/ea0022266-2193comportamiento-de-los-espanoles-ante-las-vacaciones-iii) |
94
- | | **Total** | 31318 | 1741 | 200 | |
95
-
96
-
97
- ## 🏗️ Folder structure
98
- Each folder represents one dataset. You will find the following files within:
99
-
100
- * all.parquet: the processed data, with each column tagged with our typing system, in [parquet](https://arrow.apache.org/docs/python/parquet.html).
101
- * qa.parquet: contains the human-made set of questions, tagged by type, for the dataset (sample_answer indicates the answers for DataBench lite)
102
- * info.yml: additional information about the dataset
103
-
104
- ## 🗂️ Column typing system
105
- In an effort to map the stage for later analysis, we have categorized the columns by type. This information allows us to segment different kinds of data so that we can subsequently analyze the model's behavior on each column type separately. All parquet files have been casted to their smallest viable data type using the open source [Lector](https://github.com/graphext/lector) reader.
106
-
107
- What this means is that in the data types we have more granular information that allows us to know if the column contains NaNs or not (following panda’s convention of Int vs int), as well as whether small numerical values contain negatives (Uint vs int) and their range. We also have dates with potential timezone information (although for now they’re all UTC), as well as information about categories’ cardinality coming from the arrow types.
108
-
109
- In the table below you can see all the data types assigned to each column, as well as the number of columns for each type. The most common data types are numbers and categories with 1336 columns of the total of 1615 included in DataBench. These are followed by some other more rare types as urls, booleans, dates or lists of elements.
110
-
111
- | Type | Columns | Example |
112
- | -------------- | ------- | ----------------------- |
113
- | number | 269 | 1 |
114
- | category | 1464 | banana |
115
- | date | 2 | 1979-01-01 |
116
- | text | 1 | A blue rabbit went to... |
117
- | list[number] | 1 | [10,11,12] |
118
- | list[category] | 4 | [banana, pineapple] |
119
-
120
- ## 🔗 Reference
121
-
122
- You can download the paper [here](http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6617). If you use this resource, please use the following reference:
123
-
124
- ```
125
- @article{DBLP:journals/pdln/GrijalbaLCC24,
126
- author={Jorge Osés Grijalba and Luis Alfonso Ureña López and José Camacho-Collados and Eugenio Martínez Cámara},
127
- title={Towards Quality Benchmarking in Question Answering over Tabular Data in Spanish},
128
- year={2024},
129
- cdate={1704067200000},
130
- journal={Proces. del Leng. Natural},
131
- volume={73},
132
- pages={283-296},
133
- url={http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6617}
134
- }
135
  ```
 
1
+ ---
2
+ language:
3
+ - en
4
+ - es
5
+ pretty_name: "DataBench SPAnish"
6
+ tags:
7
+ - table-question-answering
8
+ - table
9
+ - qa
10
+ license: mit
11
+ task_categories:
12
+ - table-question-answering
13
+ - question-answering
14
+ default: qa
15
+ configs:
16
+ - config_name: qa
17
+ data_files:
18
+ - ES_01_40db_Igualdad/qa.parquet
19
+ - ES_02_40dB_Dormir/qa.parquet
20
+ - ES_03_CIS_Enero_Marzo_2023/qa.parquet
21
+ - ES_04_CEA_Barometro_Andaluz_Septiembre_2023/qa.parquet
22
+ - ES_05_CIS_2023_Salud_Bienestar/qa.parquet
23
+ - ES_06_CIS_Politica_Fiscal_Julio_2023/qa.parquet
24
+ - ES_07_CIS_Relaciones_Afectivas_Pospandemia_III/qa.parquet
25
+ - ES_08_CIS_Barometro_Diciembre_2022/qa.parquet
26
+ - ES_09_40dB_Percepcion_Amor/qa.parquet
27
+ - ES_10_CIS_Salud_Mental_Pandemia_2021/qa.parquet
28
+ - config_name: iberlef
29
+ data_files:
30
+ - split: dev
31
+ path:
32
+ - ES_01_40db_Igualdad/qa.parquet
33
+ - ES_02_40dB_Dormir/qa.parquet
34
+ - ES_03_CIS_Enero_Marzo_2023/qa.parquet
35
+ - ES_04_CEA_Barometro_Andaluz_Septiembre_2023/qa.parquet
36
+ - split: train
37
+ path:
38
+ - ES_05_CIS_2023_Salud_Bienestar/qa.parquet
39
+ - ES_06_CIS_Politica_Fiscal_Julio_2023/qa.parquet
40
+ - ES_07_CIS_Relaciones_Afectivas_Pospandemia_III/qa.parquet
41
+ - ES_08_CIS_Barometro_Diciembre_2022/qa.parquet
42
+ - ES_09_40dB_Percepcion_Amor/qa.parquet
43
+ - ES_10_CIS_Salud_Mental_Pandemia_2021/qa.parquet
44
+ ---
45
+
46
+ # DataBench SPAnish
47
+
48
+ This repository contains the original 10 datasets used for the paper [Towards Quality Benchmarking in Question Answering over Tabular Data in Spanish](http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6617) which appeared in SEPLN 2024.
49
+
50
+ It is a spin-off of the original suite in English, which you can find [here](https://huggingface.co/datasets/cardiffnlp/databench).
51
+
52
+
53
+
54
+ ## Usage
55
+
56
+ ```python
57
+ from datasets import load_dataset
58
+
59
+ # Load all QA pairs
60
+ all_qa = load_dataset("SINAI/databenchSPA", name="qa")
61
+
62
+ # Load PRESTA QA splits
63
+ iberlef_train_qa = load_dataset("SINAI/databenchSPA", name="iberlef", split="train")
64
+ iberlef_dev_qa = load_dataset("SINAI/databenchSPA", name="iberlef", split="dev")
65
+
66
+ ```
67
+
68
+ You can use any of the individual [integrated libraries](https://huggingface.co/docs/hub/datasets-libraries#libraries) to load the actual data where the answer is to be retrieved.
69
+
70
+ For example, using pandas in Python:
71
+
72
+ ```python
73
+ import pandas as pd
74
+
75
+ # "ES_01_40db_Igualdad", the id of the dataset
76
+ ds_id = all_qa['dataset'][0]
77
+
78
+ # Dataset containing the answer
79
+ df = pd.read_parquet(f"hf://datasets/SINAI/databenchSPA/{ds_id}/all.parquet")
80
+ ```
81
+
82
+ | # | Name | Rows | Columns | #QA | Source (Reference) |
83
+ |----|----------------------------------------------------------------------------------------------------------------------------------------------|-------|---------|-----|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
84
+ | 1 | [Encuesta de Igualidad](https://public.graphext.com/bcf11ce000281e77/index.html?section=data) | 2000 | 105 | 20 | [40dB](https://elpais.com/espana/2024-03-11/consulte-todos-los-datos-internos-de-la-encuesta-de-el-pais-de-marzo-cuestionarios-cruces-y-respuestas.html) |
85
+ | 2 | [Calidad del Sueño](https://public.graphext.com/d586cf17f68716b2/index.html) | 2000 | 80 | 20 | [40dB](https://elpais.com/ciencia/2024-02-25/consulte-todos-los-datos-internos-del-barometro-de-el-pais-cuestionarios-cruces-y-respuestas-individuales.html) |
86
+ | 3 | [Fusión Barómetros](https://public.graphext.com/090bc5693db03f4b/index.html) | 7430 | 161 | 20 | [CIS](https://www.cis.es/es/detalle-ficha-estudio?idEstudio=14707) |
87
+ | 4 | [Barómetro Andaluz](https://public.graphext.com/ece62fc1938451e2/index.html) | 5349 | 85 | 20 | [CEA](https://www.centrodeestudiosandaluces.es/barometro/barometro-andaluz-de-septiembre-2023) |
88
+ | 5 | [Juventud](https://public.graphext.com/d47edca4181aa6ab/index.html) | 1510 | 236 | 20 | [CRS](https://www.centroreinasofia.org/publicacion/barometro-salud-2023/) |
89
+ | 6 | [Política Fiscal](https://public.graphext.com/244aabe0e1f29604/index.html?section=data) | 3011 | 198 | 20 | [CIS](https://www.cis.es/detalle-ficha-estudio?origen=estudio&idEstudio=14741) |
90
+ | 7 | [Relaciones](https://public.graphext.com/4bfd99166c878c01/index.html) | 2491 | 186 | 20 | [CIS](https://www.cis.es/detalle-ficha-estudio?origen=estudio&idEstudio=14702) |
91
+ | 8 | [Barómetro Mensual](https://public.graphext.com/6d6ed9331ce0ab03/index.html) | 2444 | 185 | 20 | [CIS](https://www.cis.es/es/detalle-ficha-estudio?idEstudio=14676) |
92
+ | 9 | [Percepción del Amor](https://public.graphext.com/0c073fc60827634b/index.html?section=data) | 2000 | 150 | 20 | [40dB](https://elpais.com/sociedad/2022-06-05/consulte-todos-los-datos-internos-de-la-encuesta-de-el-pais-sobre-la-percepcion-del-amor-cuestionarios-y-respuestas-individuales.html) |
93
+ | 10 | [Salud Mental](https://public.graphext.com/05917cf2424e681f/index.html?section=data) | 3083 | 354 | 20 | [CIS](https://datos.gob.es/es/catalogo/ea0022266-2193comportamiento-de-los-espanoles-ante-las-vacaciones-iii) |
94
+ | | **Total** | 31318 | 1741 | 200 | |
95
+
96
+
97
+ ## 🏗️ Folder structure
98
+ Each folder represents one dataset. You will find the following files within:
99
+
100
+ * all.parquet: the processed data, with each column tagged with our typing system, in [parquet](https://arrow.apache.org/docs/python/parquet.html).
101
+ * qa.parquet: contains the human-made set of questions, tagged by type, for the dataset.
102
+ * info.yml: additional information about the dataset
103
+
104
+ ## 🗂️ Column typing system
105
+ In an effort to map the stage for later analysis, we have categorized the columns by type. This information allows us to segment different kinds of data so that we can subsequently analyze the model's behavior on each column type separately. All parquet files have been casted to their smallest viable data type using the open source [Lector](https://github.com/graphext/lector) reader.
106
+
107
+ What this means is that in the data types we have more granular information that allows us to know if the column contains NaNs or not (following panda’s convention of Int vs int), as well as whether small numerical values contain negatives (Uint vs int) and their range. We also have dates with potential timezone information (although for now they’re all UTC), as well as information about categories’ cardinality coming from the arrow types.
108
+
109
+ In the table below you can see all the data types assigned to each column, as well as the number of columns for each type. The most common data types are numbers and categories with 1336 columns of the total of 1615 included in DataBench. These are followed by some other more rare types as urls, booleans, dates or lists of elements.
110
+
111
+ | Type | Columns | Example |
112
+ | -------------- | ------- | ----------------------- |
113
+ | number | 269 | 1 |
114
+ | category | 1464 | banana |
115
+ | date | 2 | 1979-01-01 |
116
+ | text | 1 | A blue rabbit went to... |
117
+ | list[number] | 1 | [10,11,12] |
118
+ | list[category] | 4 | [banana, pineapple] |
119
+
120
+ ## 🔗 Reference
121
+
122
+ You can download the paper [here](http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6617). If you use this resource, please use the following reference:
123
+
124
+ ```
125
+ @article{DBLP:journals/pdln/GrijalbaLCC24,
126
+ author={Jorge Osés Grijalba and Luis Alfonso Ureña López and José Camacho-Collados and Eugenio Martínez Cámara},
127
+ title={Towards Quality Benchmarking in Question Answering over Tabular Data in Spanish},
128
+ year={2024},
129
+ cdate={1704067200000},
130
+ journal={Proces. del Leng. Natural},
131
+ volume={73},
132
+ pages={283-296},
133
+ url={http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6617}
134
+ }
135
  ```