How does semantic analysis differ from syntactic analysis in NLP?

Semantic analysis plays a crucial role in natural language processing (NLP) as it is concerned with understanding the meaning behind words, phrases, and sentences. While syntactic analysis focuses on the structure of a sentence, checking for grammatical correctness and the relationships between words based on their arrangement, semantic analysis goes a step further to interpret what those words and structures actually convey in terms of meaning and context.

In this framework, semantic analysis utilizes various techniques to derive intended meanings, such as word sense disambiguation, handling context, and recognizing implications beyond the literal definitions of terms. This process involves understanding nuances, idioms, metaphors, and other forms of expression that contribute to the overall significance of a piece of text.

Other options, while relevant to NLP, capture different aspects of linguistic analysis. Evaluating sentence structure is strictly part of syntactic analysis. Using statistical methods pertains more to approaches in both syntactic and semantic analysis but does not define what semantic analysis itself is. Viewing semantic analysis as a lower-level analysis misrepresents its importance, as understanding meaning is often seen as a more complex and nuanced task than simply arranging words correctly.