rule-based-nlp-still-useful

IN premise — entries/2026/06/21/wiki-Natural_language_processing-chunk-1.md

Created 2026-06-21T09:50:10+00:00

Rule-based NLP systems remain useful for low-resource languages (e.g., Apertium), tokenization preprocessing, and post-processing/knowledge extraction tasks

Summary

Hand-written linguistic rules still earn their place where there isn't enough example data to train a model, where you just need to split raw text into pieces before anything else runs, and where you need to enforce hard constraints on a model's output. This means a robust NLP pipeline should treat rules as a working complement to learned models, not a relic to be discarded.