Previous work has predominantly focused on monolingual English semantic
parsing. We, instead, explore the feasibility of Chinese semantic parsing in
the absence of labeled data for Chinese meaning representations. We describe
the pipeline of automatically collecting the linearized Chinese meaning
representation data for sequential-to sequential neural networks. We further
propose a test suite designed explicitly for Chinese semantic parsing, which
provides fine-grained evaluation for parsing performance, where we aim to study
Chinese parsing difficulties. Our experimental results show that the difficulty
of Chinese semantic parsing is mainly caused by adverbs. Realizing Chinese
parsing through machine translation and an English parser yields slightly lower
performance than training a model directly on Chinese data.

本文探索了在没有中文标注数据的情况下实现中文语义分析的可行性，描述了线性化的中文意义表示数据的自动收集流程，提出了专为中文语义分析设计的测试套件，阐述了中文语义分析的困难主要是由副词引起的，经实验表明采用机器翻译和英文解析器实现中文语义分析的性能略低于直接在中文数据上训练模型。