Grammatical Relations in Chinese: GB-Ground Extraction and Data-Driven Parsing
Weiwei Sun, Yantao Du, Xin Kou, Shuoyang Ding, Xiaojun Wan · 2014
This paper is concerned with building linguistic resources and statistical parsers for deep grammatical relation (GR) analysis of Chinese texts.A set of linguistic rules is defined to explore implicit phrase structural information and thus build high-quality GR annotations that are represented as general directed dependency graphs.The reliability of this linguistically-motivated GR extraction procedure is highlighted by manual evaluation.Based on the converted corpus, we study transition-based, datadriven models for GR parsing.We present a novel transition system which suits GR graphs better than existing systems.The key idea is to introduce a new type of transition that reorders top k elements in the memory module.Evaluation gauges how successful GR parsing for Chinese can be by applying datadriven models.