|
|
--- |
|
|
dataset_info: |
|
|
features: |
|
|
- name: conversations |
|
|
list: |
|
|
- name: from |
|
|
dtype: string |
|
|
- name: value |
|
|
dtype: string |
|
|
- name: sources |
|
|
dtype: string |
|
|
- name: references |
|
|
dtype: string |
|
|
- name: language_pair |
|
|
dtype: string |
|
|
- name: dataset |
|
|
dtype: string |
|
|
splits: |
|
|
- name: train |
|
|
num_bytes: 14008918721 |
|
|
num_examples: 241828 |
|
|
download_size: 7996471024 |
|
|
dataset_size: 14008918721 |
|
|
configs: |
|
|
- config_name: default |
|
|
data_files: |
|
|
- split: train |
|
|
path: data/train-* |
|
|
license: cc-by-sa-4.0 |
|
|
task_categories: |
|
|
- translation |
|
|
language: |
|
|
- en |
|
|
- de |
|
|
- es |
|
|
- fr |
|
|
- it |
|
|
- ko |
|
|
- nl |
|
|
- pt |
|
|
- ru |
|
|
- zh |
|
|
size_categories: |
|
|
- 100K<n<1M |
|
|
--- |
|
|
# Dataset Card for DocBlocks |
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|
DocBlocks is a high-quality, multilingual document-level machine translation (MT) dataset designed to fine-tune large language models (LLMs) on long-context translation tasks. Unlike traditional sentence-level datasets, it contains full documents with natural discourse structures and contextual alignment, helping models maintain coherence, consistency, and high translation quality across longer texts. |
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- **Curated by:** Instituto Superior Técnico, Instituto de Telecomunicações, Carnegie Mellon University and Unbabel; |
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- **Language(s) (NLP):** English, German, Spanish, French, Italian, Dutch, Portuguese, Russian, Korean, Chinese; |
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- **License:** DocBlocks includes data from the following sources: **IWSLT**, **Europarl**, **News Commentary**, **GuoFeng**, and **BWB**. For licensing information, please refer to the official documentation or websites of each source. |
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### Dataset Details |
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|
* `conversations` - The user and assistant dialogue turns, following an instruction-based format suitable for LLM fine-tuning; |
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|
* `sources` - The original source text in the source language; |
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* `references` - The human-translated target/reference text in the target language; |
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* `language_pair` - The language direction of the translation pair; |
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* `dataset` - The name of the original dataset from which the document was sourced. |
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## Bias, Risks, and Limitations |
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DocBlocks may reflect linguistic, cultural, and domain biases from its source corpora, and its performance is influenced by language coverage and document structure variability. |
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## Citation |
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|
```bibtex |
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@misc{multilingual_contextualization_llm_2025, |
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title={Multilingual Contextualization of Large Language Models for Document-Level Machine Translation}, |
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|
author={Miguel Moura Ramos and Patrick Fernandes and Sweta Agrawal and André F. T. Martins}, |
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|
year={2025}, |
|
|
eprint={2504.12140}, |
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|
archivePrefix={arXiv}, |
|
|
primaryClass={cs.CL}, |
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|
url={https://arxiv.org/abs/2504.12140}, |
|
|
} |
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|
``` |
