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.
