# Natural Language Processing and LLMs

> Source: <https://www.dotnetperls.com/2026_8_4_natural-language-processing-llms>
> Published: 2026-08-04 07:00:00+00:00

After using an LLM in `llama-cpp`

to handle local tasks, I started wondering: why couldn't I write some **code** to **handle the queries** faster than the LLM inference? This might work for simple prompts, but it would fail on anything complex.

Natural Language Processing is a field of AI, and Large Language Models are a subset of NLP. The main problem with **natural languages** is that they have a lot of **complexity**—there are nearly endless edge cases.

So a simple parser written would:

• Work many times faster than an LLM.

• Fail on many prompts that an LLM might correctly handle.

• End up being an excessive amount of work with rather poor results due to the special case handling required.

Using an LLM like **Gemma 4 E4B** for natural language processing is the obvious solution. It is probably a **bad idea** to attempt to handle natural languages at all without a model that has **trained data**, due to the edge cases and quirks of languages.