Leveraging event-based
semantics for automated text simplification
Automated Text Simplification (ATS) aims to transform complex texts into
their simpler variants which are easier to understand to wider audiences and
easier to process with natural language processing (NLP) tools. While
simplification can be applied on lexical, syntactic, and discourse level, all
previously proposed ATS systems only operated on the first two levels, thus
failing at simplifying texts on the discourse level.
A few
handcrafted rules ensure that the output of the system is syntactically simple,
by placing each factual event mention in a separate short sentence, while the
state-of-the-art unsupervised lexical simplification module, based on using
word embeddings, replaces complex and infrequent words with their simpler
variants.
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