In order to use PSG in NLP for semantic analysis, you must select a suitable formalism, such as context-free grammar (CFG), head-driven phrase structure grammar (HPSG), or lexical functional grammar (LFG). Then, define the symbols and rules of your PSG and annotate them with semantic features and constraints. Afterward, parse the input sentence or text using your PSG to generate a parse tree or set of parse trees that match the syntactic structure and semantics of the input. Lastly, extract the semantic representation from the parse tree or trees, such as a logical form or a semantic graph, and perform operations like simplification, normalization, or inference. To illustrate, using a simple CFG with semantic features you can parse and analyze the sentence "She likes dogs" as follows: S[sem = likes(She, dogs)] | NP[sem = She] VP[sem = likes(NP[sem], NP[sem])] | | She V[sem = likes(NP[sem], NP[sem])] NP[sem = dogs] | | likes N[sem = dogs] | dogs. This parse tree demonstrates how the semantic features are propagated from the lexical items to higher-level constituents and how the sentence's semantic representation is derived from its features.