RaniduG/SiPaKosa-Sent

SiPaKosa: Sinhala-Pali Buddhist Corpus

A comprehensive corpus of canonical and classical Buddhist texts in Sinhala and Pali, compiled from historical archives and web-scraped canonical scriptures.

This is the sentence-level version of the SiPaKosa dataset. Where SiPaKosa contains book level text, this dataset has all sentences by book.

Related dataset (book-level): RaniduG/SiPaKosa

Dataset Statistics

• Total Sentences: 786,344
• Sinhala Sentences: 465,539 (59.2%)
• Mixed Sinhala-Pali: 320,805 (40.8%)
• Sources: 16 historical books (IFBC) + 5 Nikayas (Tripitaka)

Dataset Configs

There are four configs available:

Config	Format	Columns	Best for
sinhala	txt	text only	model training
mixed	txt	text only	model training
sinhala_metadata	csv	sentence_id, book_category, book_name_si, book_name_en, source, text, language	filtering by book or source
mixed_metadata	csv	sentence_id, book_category, book_name_si, book_name_en, source, text, language	filtering by book or source

Dataset Structure

data/
├── sinhala/
│   ├── train.txt
│   ├── train.csv
│   ├── validation.txt
│   ├── validation.csv
│   ├── test.txt
│   └── test.csv
└── mixed/
    ├── train.txt
    ├── train.csv
    ├── validation.txt
    ├── validation.csv
    ├── test.txt
    └── test.csv

CSV Columns

Column	Description	Example
sentence_id	Globally unique sentence ID	1
book_category	Category of the source book	books-related-to-the-tipitaka
book_name_si	Sinhala book name (IFBC only)	විශුද්ධිමාර්ගය
book_name_en	English book name (Tripitaka only)	Digha Nikaya
source	Data source	IFBC or Tripitaka
text	The sentence	මා හට අසන්නට ලැබුණේ...
language	Language classification	sinhala or mixed

Metadata Structure

The metadata/ folder contains two sub-folders: pdf/ and tripitaka/.

metadata/pdf/

Holds statistics and manifest data for the 16 digitised Buddhist books in the PDF corpus.

• corpus_manifest.json — lists each book with its name (Sinhala and English), category, and file paths.
• corpus_statistics.json — high-level summary: total books (16), total pages (7,064), language split (Sinhala vs. mixed), and category distribution.
• detailed_corpus_statistics.json — per-book and per-category breakdown including word counts, character counts, and averages per page. Covers three categories: books-related-to-the-tipitaka, old-books, and buddhist-characters.

metadata/tripitaka/

Contains scraped sutta data from tripitaka.online, organised by nikaya. Each nikaya has its own sub-folder (e.g., digha/, majjhima/, anguttara/).

Inside each sub-folder:

• suttas_batch_{number}.json — batched sutta records. Each entry contains the URL, title, Sinhala content, Pali content, word counts, nikaya info, scraping method, and timestamp.
• error_log.json — records any suttas that failed to scrape.
• scraping_progress.json — tracks how many suttas were scraped vs. errored.

Quick Start

from datasets import load_dataset

# Load plain text for model training
sinhala_ds = load_dataset("RaniduG/SiPaKosa", "sinhala")
print(sinhala_ds["train"][0])

mixed_ds = load_dataset("RaniduG/SiPaKosa", "mixed")
print(mixed_ds["train"][0])

# Load with metadata for filtering by book or source
sinhala_meta = load_dataset("RaniduG/SiPaKosa", "sinhala_metadata")
print(sinhala_meta["train"][0])

# Filter by source
import pandas as pd
df = pd.DataFrame(sinhala_meta["train"])
ifbc_only = df[df["source"] == "IFBC"]
tripitaka_only = df[df["source"] == "Tripitaka"]

# Filter by book
book_df = df[df["book_name_si"] == "විශුද්ධිමාර්ගය"]

Documentation

• Citation - How to cite this work

License

This dataset is released under MIT for research purposes.

Paper

https://arxiv.org/abs/2603.29221