@inproceedings{ueda-etal-2023-kwja,
title = "{KWJA}: A Unified {J}apanese Analyzer Based on Foundation Models",
author = "Ueda, Nobuhiro and
Omura, Kazumasa and
Kodama, Takashi and
Kiyomaru, Hirokazu and
Murawaki, Yugo and
Kawahara, Daisuke and
Kurohashi, Sadao",
editor = "Bollegala, Danushka and
Huang, Ruihong and
Ritter, Alan",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-demo.52",
doi = "10.18653/v1/2023.acl-demo.52",
pages = "538--548",
abstract = "We present KWJA, a high-performance unified Japanese text analyzer based on foundation models.KWJA supports a wide range of tasks, including typo correction, word segmentation, word normalization, morphological analysis, named entity recognition, linguistic feature tagging, dependency parsing, PAS analysis, bridging reference resolution, coreference resolution, and discourse relation analysis, making it the most versatile among existing Japanese text analyzers.KWJA solves these tasks in a multi-task manner but still achieves competitive or better performance compared to existing analyzers specialized for each task.KWJA is publicly available under the MIT license at \url{https://github.com/ku-nlp/kwja}.",
}
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<abstract>We present KWJA, a high-performance unified Japanese text analyzer based on foundation models.KWJA supports a wide range of tasks, including typo correction, word segmentation, word normalization, morphological analysis, named entity recognition, linguistic feature tagging, dependency parsing, PAS analysis, bridging reference resolution, coreference resolution, and discourse relation analysis, making it the most versatile among existing Japanese text analyzers.KWJA solves these tasks in a multi-task manner but still achieves competitive or better performance compared to existing analyzers specialized for each task.KWJA is publicly available under the MIT license at https://github.com/ku-nlp/kwja.</abstract>
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%0 Conference Proceedings
%T KWJA: A Unified Japanese Analyzer Based on Foundation Models
%A Ueda, Nobuhiro
%A Omura, Kazumasa
%A Kodama, Takashi
%A Kiyomaru, Hirokazu
%A Murawaki, Yugo
%A Kawahara, Daisuke
%A Kurohashi, Sadao
%Y Bollegala, Danushka
%Y Huang, Ruihong
%Y Ritter, Alan
%S Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F ueda-etal-2023-kwja
%X We present KWJA, a high-performance unified Japanese text analyzer based on foundation models.KWJA supports a wide range of tasks, including typo correction, word segmentation, word normalization, morphological analysis, named entity recognition, linguistic feature tagging, dependency parsing, PAS analysis, bridging reference resolution, coreference resolution, and discourse relation analysis, making it the most versatile among existing Japanese text analyzers.KWJA solves these tasks in a multi-task manner but still achieves competitive or better performance compared to existing analyzers specialized for each task.KWJA is publicly available under the MIT license at https://github.com/ku-nlp/kwja.
%R 10.18653/v1/2023.acl-demo.52
%U https://aclanthology.org/2023.acl-demo.52
%U https://doi.org/10.18653/v1/2023.acl-demo.52
%P 538-548
Markdown (Informal)
[KWJA: A Unified Japanese Analyzer Based on Foundation Models](https://aclanthology.org/2023.acl-demo.52) (Ueda et al., ACL 2023)
ACL
- Nobuhiro Ueda, Kazumasa Omura, Takashi Kodama, Hirokazu Kiyomaru, Yugo Murawaki, Daisuke Kawahara, and Sadao Kurohashi. 2023. KWJA: A Unified Japanese Analyzer Based on Foundation Models. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 538–548, Toronto, Canada. Association for Computational Linguistics.