Zero-shot Chinese Discourse Dependency Parsing via Cross-lingual Mapping
This addresses the challenge of discourse parsing in low-resource languages like Chinese, though it is incremental as it adapts existing cross-lingual methods.
The paper tackles the problem of discourse parsing in Chinese without labeled data by leveraging English discourse labeled data and parsing techniques, achieving automatic Chinese discourse parsing without requiring large-scale Chinese labeled data.
Due to the absence of labeled data, discourse parsing still remains challenging in some languages. In this paper, we present a simple and efficient method to conduct zero-shot Chinese text-level dependency parsing by leveraging English discourse labeled data and parsing techniques. We first construct the Chinese-English mapping from the level of sentence and elementary discourse unit (EDU), and then exploit the parsing results of the corresponding English translations to obtain the discourse trees for the Chinese text. This method can automatically conduct Chinese discourse parsing, with no need of a large scale of Chinese labeled data.