Unsupervised Paraphrasing of Multiword Expressions
Takashi Wada Yuji Matsumoto Timothy Baldwin Jey Han Lau
We propose an unsupervised approach to paraphrasing multiword expressions
(MWEs) in context. Our model employs only monolingual corpus data and
pre-trained language models (without fine-tuning), and does not make use of any
external resources such as dictionaries. We evaluate our method on the SemEval
2022 idiomatic semantic text similarity task, and show that it outperforms all
unsupervised systems and rivals supervised systems.