Meaning of phrase structure rules by Andrew Carnie

Phrase structure rules are rules that describe the hierarchical structure of sentences in a language. These rules specify how words can be combined to form phrases, and how phrases can be combined to form sentences. They help to explain the relationships between different elements in a sentence, such as subjects, verbs, objects, and modifiers. By following these rules, speakers of a language can create grammatically correct sentences that convey meaning effectively. Andrew Carnie, a linguist and author, likely refers to phrase structure rules in the context of syntax, the study of sentence structure in language.

Phrase structure rules (PSRs) are a type of linguistic rule that specify how words can be combined to form phrases and sentences. They are a fundamental part of generative grammar, a theory of language that attempts to explain how sentences are generated.

PSRs are typically written in the form of rewrite rules, which specify how a particular symbol on the left-hand side of the rule can be expanded into a sequence of symbols on the right-hand side. For example, the following PSR states that a noun phrase (NP) can be expanded into a determiner (Det) followed by a noun (N):

NP → Det N

This rule can be used to generate the noun phrase "the cat", which can be represented as follows:

NP
Det the
N cat

PSRs are used in generative grammar to generate sentences in a top-down manner, starting with a root symbol (S) and recursively expanding it into smaller and smaller constituents until a complete sentence is formed. For example, the following derivation tree shows how the sentence "The cat sat on the mat" can be generated using PSRs:

S
NP the cat
VP sat on the mat

NP
Det the
N cat

VP
V sat
PP on the mat

PP
P on
NP the mat

Det the
N mat

The rules used in this derivation are as follows:

- S → NP VP
- NP → Det N
- VP → V PP
- PP → P NP
- Det → the
- N → cat
- V → sat
- P → on

PSRs are a powerful tool for describing the structure of natural language sentences. They can be used to capture the regularities of language and to generate sentences that are grammatical and acceptable to native speakers.