Syntactic Simplification

Syntactic simplification aims to reduce the complexity of sentence structures while preserving their meaning, improving readability and accessibility. Current research explores methods leveraging semantic graphs, like Abstract Meaning Representation (AMR), to guide simplification processes, often in conjunction with large language models (LLMs) for improved performance and interpretability. These approaches are being evaluated and refined using new datasets and metrics focusing on information density and controlled simplification to minimize information loss, particularly relevant for knowledge graph construction. This work has implications for various NLP applications, including text summarization, machine translation, and accessibility tools for individuals with language processing difficulties.