|
--- |
|
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: 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: |
|
- name: train |
|
num_bytes: 2567138 |
|
num_examples: 254 |
|
download_size: 1438019 |
|
dataset_size: 2567138 |
|
- 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: |
|
- name: train |
|
num_bytes: 6020903 |
|
num_examples: 564 |
|
download_size: 3261593 |
|
dataset_size: 6020903 |
|
- config_name: comida-y-diversión |
|
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: 3602835 |
|
num_examples: 454 |
|
download_size: 1866935 |
|
dataset_size: 3602835 |
|
- config_name: computadoras-y-electrónica |
|
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: 5457681 |
|
num_examples: 821 |
|
download_size: 2647916 |
|
dataset_size: 5457681 |
|
- config_name: cuidado-y-estilo-personal |
|
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: 7368188 |
|
num_examples: 724 |
|
download_size: 4088837 |
|
dataset_size: 7368188 |
|
- 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: en-el-trabajo |
|
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: 2313935 |
|
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 |
|
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: 4311584 |
|
num_examples: 496 |
|
download_size: 2293097 |
|
dataset_size: 4311584 |
|
- 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 |
|
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: 5183587 |
|
num_examples: 459 |
|
download_size: 2761337 |
|
dataset_size: 5183587 |
|
- config_name: mascotas-y-animales |
|
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: 3224822 |
|
num_examples: 338 |
|
download_size: 1772324 |
|
dataset_size: 3224822 |
|
- 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: 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: computadoras-y-electrónica |
|
data_files: |
|
- split: train |
|
path: computadoras-y-electrónica/train-* |
|
- config_name: cuidado-y-estilo-personal |
|
data_files: |
|
- split: train |
|
path: cuidado-y-estilo-personal/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. |
|
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