README.md

---
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
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    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
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    num_examples: 7380
  download_size: 38605450
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- config_name: arte-y-entretenimiento
  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:
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    num_examples: 254
  download_size: 1438019
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- config_name: carreras-y-educación
  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:
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    num_examples: 564
  download_size: 3261593
  dataset_size: 6020903
- config_name: comida-y-diversión
  features:
  - name: category
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  - 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
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    num_examples: 454
  download_size: 1866935
  dataset_size: 3602835
- 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
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  - name: num_refs
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  - name: expert_author
    dtype: bool
  splits:
  - name: train
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    num_examples: 201
  download_size: 1028678
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- config_name: en-el-trabajo
  features:
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  - name: question
    dtype: string
  - name: introduction
    dtype: string
  - name: answers
    sequence: string
  - name: short_answers
    sequence: string
  - name: url
    dtype: string
  - name: num_answers
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  - name: num_refs
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  - name: expert_author
    dtype: bool
  splits:
  - name: train
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    num_examples: 211
  download_size: 1274004
  dataset_size: 2313935
- config_name: en-la-casa-y-el-jardín
  features:
  - name: category
    dtype: string
  - name: question
    dtype: string
  - name: introduction
    dtype: string
  - name: answers
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  - name: short_answers
    sequence: string
  - name: url
    dtype: string
  - name: num_answers
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  - name: num_refs
    dtype: int32
  - name: expert_author
    dtype: bool
  splits:
  - name: train
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  download_size: 2293097
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- config_name: filosofía-y-religión
  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: 2717929
    num_examples: 264
  download_size: 1547991
  dataset_size: 2717929
- config_name: finanzas-y-negocios
  features:
  - name: category
    dtype: string
  - name: question
    dtype: string
  - name: introduction
    dtype: string
  - name: answers
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  - 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
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    num_examples: 459
  download_size: 2761337
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- config_name: mascotas-y-animales
  features:
  - name: category
    dtype: string
  - name: question
    dtype: string
  - name: introduction
    dtype: string
  - name: answers
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  - 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:
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    num_examples: 338
  download_size: 1772324
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- 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
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    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
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    num_examples: 147
  download_size: 984068
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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: arte-y-entretenimiento
  data_files:
  - split: train
    path: arte-y-entretenimiento/train-*
- config_name: carreras-y-educación
  data_files:
  - split: train
    path: carreras-y-educación/train-*
- config_name: comida-y-diversión
  data_files:
  - split: train
    path: comida-y-diversión/train-*
- config_name: deportes
  data_files:
  - split: train
    path: deportes/train-*
- config_name: en-el-trabajo
  data_files:
  - split: train
    path: en-el-trabajo/train-*
- config_name: en-la-casa-y-el-jardín
  data_files:
  - split: train
    path: en-la-casa-y-el-jardín/train-*
- config_name: filosofía-y-religión
  data_files:
  - split: train
    path: filosofía-y-religión/train-*
- config_name: finanzas-y-negocios
  data_files:
  - split: train
    path: finanzas-y-negocios/train-*
- config_name: mascotas-y-animales
  data_files:
  - split: train
    path: mascotas-y-animales/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.