SEACrowd/nusatranslation_emot

Nusatranslation Emot数据集旨在通过在线抓取、人工翻译和母语者段落写作等方法，为印度尼西亚的12种低资源语言构建高质量语料库。这些语言包括Ambon (abs)、Bima (bhp)、Makassarese (mak)、Palembang / Musi (mui)和Rejang (rej)等。数据集支持情感分类任务，并提供了使用`datasets`和`seacrowd`库加载数据集的示例代码。数据集的目标是解决现有语料库在词汇多样性和文化相关性方面的不足，并通过实证实验证明母语者段落写作生成的语料库在词汇多样性和文化内容方面具有更高的质量。

The Nusatranslation Emot dataset aims to construct high-quality corpora for 12 underrepresented and extremely low-resource languages in Indonesia through methods such as online scraping, human translation, and paragraph writing by native speakers. These languages include Ambon (abs), Bima (bhp), Makassarese (mak), Palembang / Musi (mui), and Rejang (rej). The dataset supports the emotion classification task and provides example code for loading the dataset using the `datasets` and `seacrowd` libraries. The goal of the dataset is to address the limitations of existing corpora in terms of lexical diversity and cultural relevance, and empirical experiments demonstrate that corpora generated through paragraph writing by native speakers exhibit superior quality in terms of lexical diversity and cultural content.

原始信息汇总

数据集概述

语言

• abs
• btk
• bew
• bug
• jav
• mad
• mak
• min
• mui
• rej
• sun

支持任务

• 情感分类

数据集使用

使用 datasets 库

python from datasets import load_dataset dset = datasets.load_dataset("SEACrowd/nusatranslation_emot", trust_remote_code=True)

使用 seacrowd 库

python import seacrowd as sc

加载数据集使用默认配置

dset = sc.load_dataset("nusatranslation_emot", schema="seacrowd")

检查数据集的所有可用子集（配置名称）

print(sc.available_config_names("nusatranslation_emot"))

使用特定配置加载数据集

dset = sc.load_dataset_by_config_name(config_name="<config_name>")

数据集版本

• 源版本：1.0.0
• SEACrowd版本：2024.06.20

数据集许可证

• Creative Commons Attribution Share-Alike 4.0 International

引用

plaintext @unpublished{anonymous2023nusawrites:, title={NusaWrites: Constructing High-Quality Corpora for Underrepresented and Extremely Low-Resource Languages}, author={Anonymous}, journal={OpenReview Preprint}, year={2023}, note={anonymous preprint under review} }

@article{lovenia2024seacrowd, title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya}, year={2024}, eprint={2406.10118}, journal={arXiv preprint arXiv: 2406.10118} }