ChatGPT is a Potential Zero-Shot Dependency Parser

Boda Lin, Xinyi Zhou, Binghao Tang, Xiaocheng Gong, Si Li
10/25/2023
cs.CL

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Abstract

Pre-trained language models have been widely used in dependency parsing task and have achieved significant improvements in parser performance. However, it remains an understudied question whether pre-trained language models can spontaneously exhibit the ability of dependency parsing without introducing additional parser structure in the zero-shot scenario. In this paper, we propose to explore the dependency parsing ability of large language models such as ChatGPT and conduct linguistic analysis. The experimental results demonstrate that ChatGPT is a potential zero-shot dependency parser, and the linguistic analysis also shows some unique preferences in parsing outputs.

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Cite this paper

@article{lin2023chatgpt,
  title  = {ChatGPT is a Potential Zero-Shot Dependency Parser},
  author = {Boda Lin and Xinyi Zhou and Binghao Tang and Xiaocheng Gong and Si Li},
  year   = {2023},
  eprint = {2310.16654},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.16654v1}
}

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