Datasets:

undertheseanlp
/

UVB-v0.1

language:
  - vi
license: apache-2.0
pretty_name: UVB - Underthesea Vietnamese Books Dataset
tags:
  - vietnamese
  - books
  - fiction
  - literature
  - text-corpus
  - goodreads
  - nlp
task_categories:
  - text-generation
  - fill-mask
  - feature-extraction
size_categories:
  - 100<n<1K
annotations_creators:
  - machine-generated
language_creators:
  - found
source_datasets:
  - tmnam20/Vietnamese-Book-Corpus
  - BrightData/Goodreads-Books
dataset_info:
  features:
    - name: id
      dtype: string
    - name: title
      dtype: string
    - name: author
      dtype: string
    - name: content
      dtype: string
    - name: genres
      sequence: string
    - name: first_publish
      dtype: string
    - name: goodreads_id
      dtype: string
    - name: goodreads_url
      dtype: string
    - name: goodreads_rating
      dtype: float64
    - name: goodreads_num_ratings
      dtype: int64
  splits:
    - name: train
      num_examples: 447
  download_size: 219000000
  dataset_size: 219000000
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train.jsonl

UVB - Underthesea Vietnamese Books Dataset

A collection of 447 Vietnamese books with full text content and Goodreads metadata for NLP research.

Dataset Description

Homepage: Underthesea NLP
Repository: HuggingFace
Point of Contact: Underthesea NLP

Dataset Summary

UVB (Underthesea Vietnamese Books) is a dataset containing 447 Vietnamese books with full text content, mapped to Goodreads for metadata enrichment including genres, ratings, and publication years. The dataset is designed for Vietnamese language model training, text generation, and other NLP tasks.

Supported Tasks

Language Modeling: Pre-training or fine-tuning Vietnamese language models
Text Generation: Training models to generate Vietnamese text
Text Classification: Using genres as labels for classification tasks
Information Extraction: Extracting structured information from book texts

Languages

Vietnamese (vi)

Dataset Structure

Data Instances

{
  "id": "vn_000001",
  "title": "The DIGITAL ECONOMY 20th Anniversary Edition",
  "author": "Don Tapscott",
  "content": "The DIGITAL ECONOMY 20th Anniversary Edition Rethinking Promise and Peril...",
  "genres": ["Business", "Paradigm Shift"],
  "first_publish": "2014",
  "goodreads_id": "20722002-the-digital-economy",
  "goodreads_url": "https://www.goodreads.com/book/show/20722002-the-digital-economy",
  "goodreads_rating": 4.1,
  "goodreads_num_ratings": 29
}

Data Fields

Field	Type	Description
`id`	string	Unique identifier (e.g., vn_000001)
`title`	string	Book title
`author`	string	Author name
`content`	string	Full text content of the book
`genres`	list[string]	Book genres from Goodreads
`first_publish`	string	First publication year
`goodreads_id`	string	Goodreads book ID
`goodreads_url`	string	Goodreads URL
`goodreads_rating`	float	Goodreads rating (1-5)
`goodreads_num_ratings`	int	Number of ratings on Goodreads

Data Splits

Split	Examples
train	447

Dataset Statistics

Total books: 447
Books with genres: 230 (51.5%)
Books with publication year: 421 (94.2%)
Total size: ~209 MB

Top Genres:

Genre	Count
Non Fiction	76
Fiction	62
Romance	37
Classics	30
Novels	27
Philosophy	25
Self Help	25

Publication Year Distribution:

Period	Count
Before 1900	6
1900-1950	12
1951-1980	38
1981-2000	82
2001-2010	134
2011+	149

Dataset Creation

Source Data

Vietnamese books: tmnam20/Vietnamese-Book-Corpus
Goodreads metadata: BrightData/Goodreads-Books

Data Collection

Vietnamese books were loaded from the source corpus
Books were matched to Goodreads entries using fuzzy title/author matching
Genres and publication years were scraped from Goodreads pages
Data was merged into a single dataset with full text content

Processing Scripts

Processing scripts are included in the scripts/ directory:

map_goodreads.py - Map Vietnamese books to Goodreads entries
add_genres.py - Fetch genres from Goodreads
add_publish_date.py - Fetch first publication year
requirements.txt - Python dependencies

Usage

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("undertheseanlp/UVB-v0.1")

# Access the data
for item in dataset["train"]:
    print(f"Title: {item['title']}")
    print(f"Author: {item['author']}")
    print(f"Content: {item['content'][:200]}...")
    print(f"Genres: {item['genres']}")
    print(f"First publish: {item['first_publish']}")
    break

# Filter by genre
fiction_books = [item for item in dataset["train"] if "Fiction" in (item.get("genres") or [])]
print(f"Found {len(fiction_books)} fiction books")

Considerations for Using the Data

Social Impact

This dataset can help advance Vietnamese NLP research and applications, contributing to language technology for Vietnamese speakers.

Limitations

Book content may contain OCR errors from digitization
Genre and metadata coverage is not 100%
Some author names may include translator information

Additional Information

Licensing

Apache 2.0

Citation

@misc{uvb_dataset,
  title={UVB: Underthesea Vietnamese Books Dataset},
  author={Underthesea NLP},
  year={2026},
  publisher={HuggingFace},
  url={https://huggingface.co/datasets/undertheseanlp/UVB-v0.1}
}

Contributions

Thanks to @rain1024 for creating this dataset.