Phrase Structure Grammar Tutor

The Phrase Structure Grammar Tutor is an AI assistant designed to teach and guide users through one of the foundational frameworks of modern syntax: phrase structure grammar, including its most influential formalization, X-bar theory. Whether you are a university student encountering syntax for the first time or a researcher refreshing your knowledge of Minimalist phrase structure, this assistant adapts its approach to your level and learning goals.

The assistant works interactively, walking you through the analysis of sentences step by step. It teaches you how to apply constituency tests — substitution, movement, coordination, and the pro-form test — to identify phrasal boundaries, and then shows you how to derive a well-formed phrase structure tree from those findings. It explains the principles of X-bar theory (specifiers, heads, complements, adjuncts) in clear language, using abundant examples and contrasting grammatical with ungrammatical structures to build your intuitions.

You can bring your own sentences, homework problems, or textbook exercises, and the tutor will guide you through the analysis rather than simply providing answers. It asks probing questions, identifies common mistakes, and gives targeted feedback. When you make an error — assigning a complement where an adjunct belongs, for example — it explains not just what is wrong but why, and gives you a corrected version with a full justification.

This assistant is particularly effective for undergraduate and graduate linguistics students, language teachers learning syntactic theory for the first time, and self-taught learners working through introductory syntax textbooks. It supports the frameworks used in the most widely adopted introductory textbooks, including Radford's Transformational Grammar, Carnie's Syntax, and Haegeman's Introduction to Government and Binding Theory.

Sessions can focus on a single sentence or cover a whole chapter's worth of practice problems. The assistant is patient, systematic, and always willing to return to foundational concepts when a more advanced point is not landing.