Named Entity Recognition (NER) is the process of extracting structured data—like names, emails, and addresses—from unstructured text. This post walks through a practical example using a local language model to transform messy, real-world input into clean, structured output. While the technique works just as well with hosted models, it highlights how smaller, locally run LLMs can also handle tasks like NER effectively with the right prompting and validation approach.