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SEACrowd/id_wsd

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Hugging Face2024-06-24 更新2024-03-04 收录
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https://hf-mirror.com/datasets/SEACrowd/id_wsd
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资源简介:
Id Wsd数据集是一个用于词义消歧任务的数据集,数据来源于新闻网站并经过人工标注。数据集中的单词通过形态分析处理以获取词元,并提取了目标词周围的词、最近的动词、及物动词和文档上下文作为特征。该数据集支持印尼语,可以通过`datasets`库或`seacrowd`库加载。

Id Wsd数据集是一个用于词义消歧任务的数据集,数据来源于新闻网站并经过人工标注。数据集中的单词通过形态分析处理以获取词元,并提取了目标词周围的词、最近的动词、及物动词和文档上下文作为特征。该数据集支持印尼语,可以通过`datasets`库或`seacrowd`库加载。
提供机构:
SEACrowd
原始信息汇总

数据集概述

语言

  • 印度尼西亚语 (ind)

任务类别

  • 词义消歧 (Word Sense Disambiguation)

数据集使用

使用 datasets

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

使用 seacrowd

python import seacrowd as sc

使用默认配置加载数据集

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

检查数据集的所有可用子集(配置名称)

print(sc.available_config_names("id_wsd"))

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

  • 未知

引用

plaintext @inproceedings{mahendra-etal-2018-cross, title = "Cross-Lingual and Supervised Learning Approach for {I}ndonesian Word Sense Disambiguation Task", author = "Mahendra, Rahmad and Septiantri, Heninggar and Wibowo, Haryo Akbarianto and Manurung, Ruli and Adriani, Mirna", booktitle = "Proceedings of the 9th Global Wordnet Conference", month = jan, year = "2018", address = "Nanyang Technological University (NTU), Singapore", publisher = "Global Wordnet Association", url = "https://aclanthology.org/2018.gwc-1.28", pages = "245--250", abstract = "Ambiguity is a problem we frequently face in Natural Language Processing. Word Sense Disambiguation (WSD) is a task to determine the correct sense of an ambiguous word. However, research in WSD for Indonesian is still rare to find. The availability of English-Indonesian parallel corpora and WordNet for both languages can be used as training data for WSD by applying Cross-Lingual WSD method. This training data is used as an input to build a model using supervised machine learning algorithms. Our research also examines the use of Word Embedding features to build the WSD model.", }

@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} }

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