Datasets:
File size: 10,305 Bytes
5fe44a1 5b1b3c1 fb77dc6 5b1b3c1 fb77dc6 5b1b3c1 fb77dc6 5b1b3c1 fb77dc6 27d4beb 2979c34 fb77dc6 5edf8ff f96edee a15a0b4 2979c34 55d65cb 934c9e6 fb77dc6 27d4beb fb77dc6 5edf8ff f96edee a15a0b4 2979c34 55d65cb 934c9e6 5fe44a1 5b1b3c1 10ad3cb 5b1b3c1 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 |
---
language: es
license: cc-by-nc-sa-3.0
multilinguality: monolingual
size_categories: 1K<n<10K
task_categories:
- text-classification
- question-answering
- conversational
- summarization
pretty_name: WikiHow-ES
tags:
- Spanish
- WikiHow
- Wiki Articles
- Tutorials
- Step-By-Step
- Instruction Tuning
dataset_info:
- config_name: adolescentes
features:
- name: category
dtype: string
- name: question
dtype: string
- name: introduction
dtype: string
- name: answers
sequence: string
- name: short_answers
sequence: string
- name: url
dtype: string
- name: num_answers
dtype: int32
- name: num_refs
dtype: int32
- name: expert_author
dtype: bool
splits:
- name: train
num_bytes: 1991245
num_examples: 201
download_size: 1153947
dataset_size: 1991245
- config_name: all
features:
- name: category
dtype: string
- name: question
dtype: string
- name: introduction
dtype: string
- name: answers
sequence: string
- name: short_answers
sequence: string
- name: url
dtype: string
- name: num_answers
dtype: int32
- name: num_refs
dtype: int32
- name: expert_author
dtype: bool
splits:
- name: train
num_bytes: 70513673
num_examples: 7380
download_size: 38605450
dataset_size: 70513673
- config_name: deportes
features:
- name: category
dtype: string
- name: question
dtype: string
- name: introduction
dtype: string
- name: answers
sequence: string
- name: short_answers
sequence: string
- name: url
dtype: string
- name: num_answers
dtype: int32
- name: num_refs
dtype: int32
- name: expert_author
dtype: bool
splits:
- name: train
num_bytes: 1935432
num_examples: 201
download_size: 1028678
dataset_size: 1935432
- config_name: pasatiempos
features:
- name: category
dtype: string
- name: question
dtype: string
- name: introduction
dtype: string
- name: answers
sequence: string
- name: short_answers
sequence: string
- name: url
dtype: string
- name: num_answers
dtype: int32
- name: num_refs
dtype: int32
- name: expert_author
dtype: bool
splits:
- name: train
num_bytes: 6366593
num_examples: 729
download_size: 3430327
dataset_size: 6366593
- config_name: relaciones
features:
- name: category
dtype: string
- name: question
dtype: string
- name: introduction
dtype: string
- name: answers
sequence: string
- name: short_answers
sequence: string
- name: url
dtype: string
- name: num_answers
dtype: int32
- name: num_refs
dtype: int32
- name: expert_author
dtype: bool
splits:
- name: train
num_bytes: 4053092
num_examples: 388
download_size: 2270175
dataset_size: 4053092
- config_name: salud
features:
- name: category
dtype: string
- name: question
dtype: string
- name: introduction
dtype: string
- name: answers
sequence: string
- name: short_answers
sequence: string
- name: url
dtype: string
- name: num_answers
dtype: int32
- name: num_refs
dtype: int32
- name: expert_author
dtype: bool
splits:
- name: train
num_bytes: 8334993
num_examples: 804
download_size: 4538289
dataset_size: 8334993
- config_name: viajes
features:
- name: category
dtype: string
- name: question
dtype: string
- name: introduction
dtype: string
- name: answers
sequence: string
- name: short_answers
sequence: string
- name: url
dtype: string
- name: num_answers
dtype: int32
- name: num_refs
dtype: int32
- name: expert_author
dtype: bool
splits:
- name: train
num_bytes: 1509893
num_examples: 139
download_size: 851347
dataset_size: 1509893
- config_name: vida-familiar
features:
- name: category
dtype: string
- name: question
dtype: string
- name: introduction
dtype: string
- name: answers
sequence: string
- name: short_answers
sequence: string
- name: url
dtype: string
- name: num_answers
dtype: int32
- name: num_refs
dtype: int32
- name: expert_author
dtype: bool
splits:
- name: train
num_bytes: 1743050
num_examples: 147
download_size: 984068
dataset_size: 1743050
configs:
- config_name: adolescentes
data_files:
- split: train
path: adolescentes/train-*
- config_name: all
data_files:
- split: train
path: all/train-*
default: true
- config_name: deportes
data_files:
- split: train
path: deportes/train-*
- config_name: pasatiempos
data_files:
- split: train
path: pasatiempos/train-*
- config_name: relaciones
data_files:
- split: train
path: relaciones/train-*
- config_name: salud
data_files:
- split: train
path: salud/train-*
- config_name: viajes
data_files:
- split: train
path: viajes/train-*
- config_name: vida-familiar
data_files:
- split: train
path: vida-familiar/train-*
---
### Dataset Summary
Articles retrieved from the [Spanish WikiHow website](https://es.wikihow.com) on September 2023.
Each article contains a tutorial about a specific topic. The format is always a "How to" question
followed by a detailed step-by-step explanation. In some cases, the response includes several methods.
The main idea is to use this data for instruction tuning of Spanish LLMs, but given its nature it
could also be used for other tasks such as text classification or summarization.
### Languages
- Spanish (ES)
### Usage
To load the full dataset:
```python
from datasets import load_dataset
all_articles = load_dataset("mapama247/wikihow_es", trust_remote_code=True)
print(all_articles.num_rows) # output: {'train': 7380}
```
To load only examples from a specific category:
```python
from datasets import load_dataset
sports_articles = load_dataset("mapama247/wikihow_es", "deportes")
print(sports_articles.num_rows) # output: {'train': 201}
```
List of available categories, with the repective number of examples:
```
computadoras-y-electrónica 821
salud 804
pasatiempos 729
cuidado-y-estilo-personal 724
carreras-y-educación 564
en-la-casa-y-el-jardín 496
finanzas-y-negocios 459
comida-y-diversión 454
relaciones 388
mascotas-y-animales 338
filosofía-y-religión 264
arte-y-entretenimiento 254
en-el-trabajo 211
adolescentes 201
deportes 201
vida-familiar 147
viajes 139
automóviles-y-otros-vehículos 100
días-de-fiesta-y-tradiciones 86
```
### Supported Tasks
This dataset can be used to train a model for...
- `instruction-tuning`
- `text-classification`
- `question-answering`
- `conversational`
- `summarization`
## Dataset Structure
### Data Instances
```python
{
'category': str,
'question': str,
'introduction': str,
'answers': List[str],
'short_answers': List[str],
'url': str,
'num_answers': int,
'num_refs': int,
'expert_author': bool,
}
```
### Data Fields
- `category`: The category (from [this list](https://es.wikihow.com/Especial:CategoryListing)) to which the example belongs to.
- `label`: Numerical representation of the category, for text classification purposes.
- `question`: The article's title, which always starts with "¿Cómo ...".
- `introduction`: Introductory text that precedes the step-by-step explanation.
- `answers`: List of complete answers, with the full explanation of each step.
- `short_answers`: List of shorter answers that only contain one-sentence steps.
- `num_answers`: The number of alternative answers provided (e.g. length of `answers`).
- `num_ref`: Number of references provided in the article.
- `expert_authors`: Whether the article's author claims to be an expert on the topic or not.
- `url`: The URL address of the original article.
### Data Splits
There is only one split (`train`) that contains a total of 7,380 examples.
## Dataset Creation
### Curation Rationale
This dataset was created for language model alignment to end tasks and user preferences.
### Source Data
How-To questions with detailed step-by-step answers, retrieved from the WikiHow website.
#### Data Collection and Normalization
All articles available in September 2023 were extracted, no filters applied.
Along with the article's content, some metadata was retrieved as well.
#### Source language producers
WikiHow users. All the content is human-generated.
### Personal and Sensitive Information
The data does not include personal or sensitive information.
## Considerations
### Social Impact
The Spanish community can benefit from the high-quality data provided by this dataset.
### Bias
No post-processing steps have been applied to mitigate potential social biases.
## Additional Information
### Curators
Marc Pàmes @ Barcelona Supercomputing Center.
### License
This dataset is licensed under a **Creative Commons CC BY-NC-SA 3.0** license.
Quote from [WikiHow's Terms of Use](https://www.wikihow.com/wikiHow:Terms-of-Use):
> All text posted by Users to the Service is sub-licensed by wikiHow to other Users under a Creative Commons license as
> provided herein. The Creative Commons license allows such user generated text content to be used freely for personal,
> non-commercial purposes, so long as it is used and attributed to the original author as specified under the terms of
> the license. Allowing free republication of our articles helps wikiHow achieve its mission by providing instruction
> on solving the problems of everyday life to more people for free. In order to support this goal, wikiHow hereby grants
> each User of the Service a license to all text content that Users contribute to the Service under the terms and
> conditions of a Creative Commons CC BY-NC-SA 3.0 License. Please be sure to read the terms of the license carefully.
> You continue to own all right, title, and interest in and to your User Content, and you are free to distribute it as
> you wish, whether for commercial or non-commercial purposes.
|