OpenSakura/OpenSakura-DS-260220-LN-ja-zh-ALIGNED-Eve

OpenSakura Eve LN Aligned Dataset

OpenSakura-DS-260220-LN-ja-zh-ALIGNED-Eve is a Japanese-to-Chinese light-novel translation dataset in OpenSakura ALIGNED format. Stats below are computed from the actual generated parquet files.

Dataset Summary

Split Information

Public Schema

Each row contains:

• —uuid (string)
• —source_text (string)
• —target_text (string)
• —source_lang (string)
• —target_lang (string)
• —glossary_uuid (string | null)
• —glossary (list[struct{term, translation, comment}])
• —gen_model, gen_frequency_penalty, gen_max_tokens, gen_temperature, gen_top_p
• —input_tokens_count (int64), output_tokens_count (int64)

Tokenization and Generation Metadata

The following fields are included to make downstream filtering/debugging easier:

• —Token counts are computed with tokenizer model zai-org/GLM-4.7.
• —Generation metadata for this release:
• —gen_model: GLM-4.7
• —gen_max_tokens: 10240
• —gen_temperature: 0.6
• —gen_top_p: 0.95
• —gen_frequency_penalty: 0.0

Usage

from datasets import load_dataset

dataset = load_dataset("OpenSakura/OpenSakura-DS-260220-LN-ja-zh-ALIGNED-Eve")
train = load_dataset("OpenSakura/OpenSakura-DS-260220-LN-ja-zh-ALIGNED-Eve", split="train")

Acknowledgments

This dataset would not exist without the generous support and contributions of the following individuals:

• —@ixgbe -- Professional guidance and hands-on help with Kubernetes infrastructure that powers the OpenSakura pipeline.
• —An anonymous group member -- Generous sponsorship of H200 compute nodes. Without their support, OpenSakura could not have been founded and this dataset could not have been produced.
• —@Josepha -- Invaluable contributions to dataset cleaning and processing techniques that shaped the quality of this release.
• —@lildub -- LLM API sponsorship during the early experimental stage of the project, enabling the initial research and prototyping.
• —[@neavo](https://github.com/neavo) -- Inspiration and solid implementation of the LinguaGacha open-source project, which informed the design of the translation API used in this project.

Limitations and Intended Use

• —Machine-generated translations may contain errors, inconsistencies, or noise.
• —Target Chinese may contain mixed script variants depending on upstream language tags.
• —Light-novel content may include mature/sensitive text (violence/sexual content/profanity).
• —Intended for research/model development; evaluate upstream rights and redistribution constraints before commercial use.