"Beyond the limitations of AI shape outputs, experience a clear and visual Syntax Tree based on traditional linguistics."

Unlike general parsers that display simplified tags optimized only for computer processing, SG SyntaxTree is designed to help English learners and researchers intuitively understand the true structure of sentences.

Going beyond simple part-of-speech classification, it faithfully reflects the systems of world-renowned grammar reference books such as The Cambridge Grammar of the English Language and Quirk et al.'s A Comprehensive Grammar of the English Language. Detailed syntactic explanations (case, tense, sentence component roles, etc.) are displayed at the bottom of each tag, enabling precise structure learning.

Overly simplified tags (such as Penn Treebank) commonly used in general computational linguistics have limitations when learning fine-grained grammatical structures. SG SyntaxTree adopts a diverse and rich set of tags optimized for educational and learning purposes, allowing you to clearly understand the hierarchical structure and dependency relations of sentences.

When asking AI to construct a grammar tree, it often outputs text as ASCII art or broken formatting, making it difficult to grasp the structure at a glance. SG SyntaxTree draws an interactive graphic tree that neatly organizes sentence structures for instant clarity.

English Learners / Test-takers: Anyone who wants to visually master complex 5-sentence-pattern structures, dummy subject-real subject relations, and clause structures.

English Educators / Instructors: Anyone who wants to present precise grammatical structures to students visually and clearly.

Linguistics / English Language and Literature Majors: Anyone who needs sophisticated syntactic analysis data based on an authoritative grammar framework.