Summary: Exploring the relevance of semantic representations in the LLM era, this study challenges the traditional roles by suggesting a reevaluation. The proposed AMR-driven ‘chain-of-thought’, termed ‘AMRCoT’, displays mixed results across varying tasks, underlining the complexity of integrating semantic layers with LLM outputs. Further research could enhance LLM performance by refining how they process and integrate semantic data, focusing efforts on multi-word expressions and named entities which typically present greater challenges.

Key Points:

• Investigation into the impact of AMR across five diver…