A Pilot Study on Dialogue-Level Dependency Parsing for Chinese
Gongyao Jiang, Shuang Liu, Meishan Zhang, Min Zhang · 2023
Dialogue-level dependency parsing has received insufficient attention, especially for Chinese.To this end, we draw on ideas from syntactic dependency and rhetorical structure theory (RST), developing a high-quality humanannotated corpus, which contains 850 dialogues and 199,803 dependencies.Considering that such tasks suffer from high annotation costs, we investigate zero-shot and fewshot scenarios.Based on an existing syntactic treebank, we adopt a signal-based method to transform seen syntactic dependencies into unseen ones between elementary discourse units (EDUs), where the signals are detected by masked language modeling.Besides, we apply single-view and multi-view data selection to access reliable pseudo-labeled instances.Experimental results show the effectiveness of these baselines.Moreover, we discuss several crucial points about our dataset and approach.