Datasets:
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: 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: 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
configs:
- config_name: all
data_files:
- split: train
path: all/train-*
default: true
- config_name: salud
data_files:
- split: train
path: salud/train-*
Dataset Summary
Articles retrieved from the Spanish WikiHow website 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:
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:
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-tuningtext-classificationquestion-answeringconversationalsummarization
Dataset Structure
Data Instances
{
'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) 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 ofanswers).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:
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.