Search Results for author: Jingsi Yu

Found 2 papers, 0 papers with code

汉语增强依存句法自动转换研究(Transformation of Enhanced Dependencies in Chinese)

no code implementations CCL 2022 Jingsi Yu, Shi Jialu, Liner Yang, Dan Xiao, Erhong Yang

“自动句法分析是自然语言处理中的一项核心任务, 受限于依存句法中每个节点只能有一条入弧的规则, 基础依存句法中许多实词之间的关系无法用依存弧和依存标签直接标明;同时, 已有的依存句法体系中的依存关系还有进一步细化、提升的空间, 以便从中提取连贯的语义关系。面对这种情况, 本文在斯坦福基础依存句法规范的基础上, 研制了汉语增强依存句法规范, 主要贡献在于:介词和连词的增强、并列项的传播、句式转换和特殊句式的增强。此外, 本文提供了基于Python的汉语增强依存句法转换的转换器, 以及一个基于Web的演示, 该演示将句子从基础依存句法树通过本文的规范解析成依存图。最后, 本文探索了增强依存句法的实际应用, 并以搭配抽取和信息抽取为例进行相关讨论。”

Cross-domain Chinese Sentence Pattern Parsing

no code implementations26 Feb 2024 Jingsi Yu, Cunliang Kong, Liner Yang, Meishan Zhang, Lin Zhu, Yujie Wang, Haozhe Lin, Maosong Sun, Erhong Yang

Sentence Pattern Structure (SPS) parsing is a syntactic analysis method primarily employed in language teaching. Existing SPS parsers rely heavily on textbook corpora for training, lacking cross-domain capability. To overcome this constraint, this paper proposes an innovative approach leveraging large language models (LLMs) within a self-training framework.

Sentence

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