Today, I embarked on an exciting journey into natural language processing by creating a syntax tree application using Python’s NLTK library. The project started by demonstrating the significance of syntax in NLP, where I built a simple Python script that tokenizes input sentences, performs POS tagging, and uses a regular-expression-based grammar to generate syntax trees. This approach provided a clear, structured visualisation of how sentences are parsed, setting a strong foundation for the project. With the core NLP functionality in place, I integrated a web interface using Flask, allowing users to enter sentences and see their parsed syntax trees in real time. To elevate the user experience, I turned to D3.js to create an interactive, horizontally oriented SVG visualisation. This step involved dynamically sizing the SVG based on the tree’s layout and adding zoom and pan features so that users could easily navigate through complex trees. The result was a sleek, responsive display that brought the underlying language structure to life.

To add a final touch of interactivity and polish, I implemented smooth hover animations and tooltips for each node in the tree. When a user hovers over a node, its circle gently enlarges while a tooltip appears, providing detailed information about the node. Throughout this process, I ensured that all text elements maintained a clean and modern appearance. This project not only deepened my understanding of NLP and web visualisation but also showcased how to seamlessly merge backend processing with interactive front-end design.