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With the recent success and popularity of pre-trained language models (LMs)in natural language processing, there has been a rise in efforts to understandtheir inner workings. In line with such interest, we propose a novel methodthat assists us in investigating the extent to which pre-trained LMs capturethe syntactic notion of constituency. Our method provides an effective way ofextracting constituency trees from the pre-trained LMs without training. Inaddition, we report intriguing findings in the induced trees, including thefact that pre-trained LMs outperform other approaches in correctly demarcatingadverb phrases in sentences.

Are Pre-trained Language Models Aware of Phrases? Simple but Strong Baselines for Grammar Induction