Structured Natural Language Processing (XNLP) is an important subset of NLP that entails understanding the underlying semantic or syntactic structure of texts, which serves as a foundational component for many downstream applications. Despite certain recent efforts to explore universal solutions for specific categories of XNLP tasks, a comprehensive and effective approach for unifying all XNLP tasks long remains underdeveloped. In the meanwhile, while XNLP demonstration systems are vital for researchers exploring various XNLP tasks, existing platforms can be limited to, e.g., supporting few XNLP tasks, lacking interactivity and universalness. To this end, we propose an advanced XNLP demonstration platform, where we propose leveraging LLM to achieve universal XNLP, with one model for all with high generalizability. Overall, our system advances in multiple aspects, including universal XNLP modeling, high performance, interpretability, scalability, and interactivity, providing a unified platform for exploring diverse XNLP tasks in the community. XNLP is online: https://xnlp.haofei.vip

翻译：结构化自然语言处理（XNLP）是自然语言处理的重要分支，旨在理解文本底层的语义或句法结构，这是许多下游应用的基础组件。尽管近期已有一些针对特定类别XNLP任务的通用解决方案探索，但能够统一所有XNLP任务的全面有效方法长期以来仍未充分发展。同时，虽然XNLP演示系统对研究人员探索各类XNLP任务至关重要，但现有平台往往存在局限，例如仅支持少量XNLP任务、缺乏交互性与普适性。为此，我们提出一个先进的XNLP演示平台，通过利用大语言模型实现通用XNLP，以单一高泛化性模型适配所有任务。总体而言，我们的系统在通用XNLP建模、高性能、可解释性、可扩展性和交互性等多方面取得进展，为学界探索多样化XNLP任务提供了统一平台。XNLP已上线：https://xnlp.haofei.vip