A Pilot Study on Dialogue-Level Dependency Parsing for Chinese

• URL: http://arxiv.org/abs/2305.12441v2
• Date: Thu, 1 Jun 2023 03:03:43 GMT
• Title: A Pilot Study on Dialogue-Level Dependency Parsing for Chinese
• Authors: Gongyao Jiang, Shuang Liu, Meishan Zhang, Min Zhang
• Abstract summary: We develop a high-quality human-annotated corpus, which contains 850 dialogues and 199,803 dependencies. Considering that such tasks suffer from high annotation costs, we investigate zero-shot and few-shot scenarios. Based on an existing syntactic treebank, we adopt a signal-based method to transform seen syntactic dependencies into unseen ones.
• Score: 21.698966896156087
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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 human-annotated corpus, which contains 850 dialogues and 199,803 dependencies. Considering that such tasks suffer from high annotation costs, we investigate zero-shot and few-shot 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.

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