SEACrowd/khmer_alt_pos
收藏Khmer Alt Pos 数据集概述
基本信息
- 数据集名称: Khmer Alt Pos
- 语言: 高棉语 (khm)
- 任务类别: 词性标注 (pos-tagging)
- 标签: 词性标注 (pos-tagging)
- 数据集版本:
- 源版本: 1.1.0
- SEACrowd版本: 2024.06.20
- 许可证: Creative Commons Attribution Non Commercial Share Alike 4.0 (cc-by-nc-sa-4.0)
数据集描述
- 数据内容: 包含20,000句高棉语语料，带有手动分词和词性标注注释。
数据集使用
使用 datasets 库
python from datasets import load_dataset dset = datasets.load_dataset("SEACrowd/khmer_alt_pos", trust_remote_code=True)
使用 seacrowd 库
python import seacrowd as sc
使用默认配置加载数据集
dset = sc.load_dataset("khmer_alt_pos", schema="seacrowd")
查看数据集的所有可用子集（配置名称）
print(sc.available_config_names("khmer_alt_pos"))
使用特定配置加载数据集
dset = sc.load_dataset_by_config_name(config_name="<config_name>")
引用
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Khmer Alt Pos 数据集:
@article{10.1145/3464378, author = {Kaing, Hour and Ding, Chenchen and Utiyama, Masao and Sumita, Eiichiro and Sam, Sethserey and Seng, Sopheap and Sudoh, Katsuhito and Nakamura, Satoshi}, title = {Towards Tokenization and Part-of-Speech Tagging for Khmer: Data and Discussion}, year = {2021}, issue_date = {November 2021}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, volume = {20}, number = {6}, issn = {2375-4699}, url = {https://doi.org/10.1145/3464378}, doi = {10.1145/3464378}, abstract = {As a highly analytic language, Khmer has considerable ambiguities in tokenization and part-of-speech (POS) tagging processing. This topic is investigated in this study. Specifically, a 20,000-sentence Khmer corpus with manual tokenization and POS-tagging annotation is released after a series of work over the last 4 years. This is the largest morphologically annotated Khmer dataset as of 2020, when this article was prepared. Based on the annotated data, experiments were conducted to establish a comprehensive benchmark on the automatic processing of tokenization and POS-tagging for Khmer. Specifically, a support vector machine, a conditional random field (CRF), a long short-term memory (LSTM)-based recurrent neural network, and an integrated LSTM-CRF model have been investigated and discussed. As a primary conclusion, processing at morpheme-level is satisfactory for the provided data. However, it is intrinsically difficult to identify further grammatical constituents of compounds or phrases because of the complex analytic features of the language. Syntactic annotation and automatic parsing for Khmer will be scheduled in the near future.}, journal = {ACM Trans. Asian Low-Resour. Lang. Inf. Process.}, month = {sep}, articleno = {104}, numpages = {16}, keywords = {annotated data, tokenization, POS-tagging, Khmer, machine learning} }
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SEACrowd 数据集:
@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} }
