neural-nlp-eliminated-feature-engineering
IN premise — entries/2026/06/21/wiki-Natural_language_processing-chunk-1.md
Created 2026-06-21T09:50:10+00:00
Neural network NLP (from ~2015) replaced manual feature engineering with learned representations, making intermediate pipeline steps like POS tagging and dependency parsing unnecessary for many tasks
Summary
Around 2015, neural networks started learning their own useful representations of language directly from raw text, which meant you no longer had to hand-build intermediate steps like tagging parts of speech or parsing sentence structure before tackling a task. This collapsed what used to be a multi-stage pipeline into a single model, cutting out error propagation between stages and making it far easier to build competitive language tools.