Semantic Task

Semantic tasks in natural language processing (NLP) focus on understanding the meaning and relationships within text, aiming to enable computers to process language more like humans. Current research emphasizes leveraging large language models (LLMs) for semantic understanding, but also explores the complementary role of structured semantic representations like Abstract Meaning Representation (AMR) graphs, particularly for improving LLM performance and interpretability in tasks such as syntactic simplification and knowledge learning. These advancements are significant because they improve the accuracy and efficiency of NLP systems across diverse applications, from machine translation and question answering to more nuanced tasks like idiom identification and semantic scene description from images.