2023
ACL
ACL 2023
KWJA: A Unified Japanese Analyzer Based on Foundation Models
Abstract
AbstractWe 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.
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Interdisciplinary Bridge
- Artificial Intelligence and Natural Language Processing
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Trend Setter
- Natural Language Processing
Authors
Topics
Artificial Intelligence > Core AI > Foundation Models
Natural Language Processing
Natural Language Processing > Understanding > Named Entity Recognition
Natural Language Processing > Understanding > Parsing
Deep Learning > Models > Foundation Models
Deep Learning > Learning Types > Multi-Task Learning
Natural Language Processing > Applications > Natural Language Processing