Natural Language Processing (NLP) is a field at the intersection of linguistics, computer science, and artificial intelligence. It focuses on enabling computers to understand, interpret, and generate human language — whether spoken or written.

How NLP Works

There are two main approaches to NLP: rule-based and machine learning-based.

In rule-based (or lexicon-based) NLP, language is broken down into tokens (words, punctuation, or morphemes), and systems apply hand-written rules or consult dictionaries to interpret meaning or perform tasks. For example, a sentiment analysis tool might check for specific keywords like “excellent” or “terrible” and follow grammar patterns to detect tone or intent. This approach is common in domains where precision and control are important.

In machine learning-based NLP, algorithms are trained on large amounts of text data. Like rule-based systems, they also tokenize input, but instead of following fixed rules, they learn from patterns in language. Transformer models like those behind ChatGPT use context from entire sentences or paragraphs to understand and generate more natural responses.

Many modern systems combine both approaches, depending on the task and domain.

Why NLP Matters

NLP powers many everyday tools: search engines, translation apps, chatbots, and writing assistants. It helps businesses analyze feedback, supports multilingual communication, and enables AI to engage in more natural conversations. But it also raises important questions about fairness, bias, and sustainability.

Real-World Examples

• DeepL uses NLP for accurate, context-aware translation.
• ChatGPT generates human-like responses across multiple languages.
• Grammarly suggests writing improvements using NLP-based grammar analysis.

NLP is what allows AI to “understand” us. Whether through simple rules or powerful AI models, it’s shaping how we interact across languages and platforms. Knowing how it works helps us use it better — and more responsibly.

Curious how NLP powers tools like ChatGPT?

Understanding Large Language Models is the next step. These advanced AI systems take NLP to the next level — learning from billions of words to generate human-like text.

👉 Read the next article: What is a Large Language Model (LLM)?