摘要：Lexical Simplification is the process of replacing complex words in a given sentence with simpler alternatives of equivalent meaning. This task has wide applicability both as an assistive technology for readers with cognitive impairments or disabilities, such as Dyslexia and Aphasia, and as a pre-processing tool for other Natural Language Processing tasks, such as machine translation and summarisation. The problem is commonly framed as a pipeline of four steps: the identification of complex words, the generation of substitution candidates, the selection of those candidates that fit the context, and the ranking of the selected substitutes according to their simplicity. In this survey we review the literature for each step in this typical Lexical Simplification pipeline and provide a benchmarking of existing approaches for these steps on publicly available datasets. We also provide pointers for datasets and resources available for the task.
